Notebook 4 of 5: Statistical Analysis

Dependencies

Location of files and macros

In [1]:
libname files "/mnt/hgfs/myfolders";
libname macros "/mnt/hgfs/myfolders/macros";
Out[1]:

11   ods listing close;ods html5 file=stdout options(bitmap_mode='inline') device=png; ods graphics on / outputfmt=png;
NOTE: Writing HTML5 Body file: STDOUT
12
13 libname files "/mnt/hgfs/myfolders";
NOTE: Libref FILES was successfully assigned as follows:
Engine: V9
Physical Name: /mnt/hgfs/myfolders
14 libname macros "/mnt/hgfs/myfolders/macros";
NOTE: Libref MACROS was successfully assigned as follows:
Engine: V9
Physical Name: /mnt/hgfs/myfolders/macros
15 ods html5 close;ods listing;

16

The following macro finds a mean value (%positive cells) for the entire pancreas vs. head, body, and tail. This is needed for ESM figure 1 & 3, supp table 2, and figure 1.

In [2]:
%macro mean (A,B);

/*find a mean value (%positive cells) for the entire pancreas vs. head, body, and tail*/

PROC means data=&A nway noprint;
     class case hospbin age_group oppc_ageR;
     var &B;
     output out=&A%quote(_mean) (drop=_type_ _freq_) mean=mean_pancreas;
run;

%mend mean;
Out[2]:

18   ods listing close;ods html5 file=stdout options(bitmap_mode='inline') device=png; ods graphics on / outputfmt=png;
NOTE: Writing HTML5 Body file: STDOUT
19
20 %macro mean (A,B);
21
22 /*find a mean value (%positive cells) for the entire pancreas vs. head, body, and tail*/
23
24 PROC means data=&A nway noprint;
25 class case hospbin age_group oppc_ageR;
26 var &B;
27 output out=&A%quote(_mean) (drop=_type_ _freq_) mean=mean_pancreas;
28 run;
29
30 %mend mean;
31 ods html5 close;ods listing;

32

Data Readiness

Import and transform dataset files

CD45 dataset

In [32]:
DATA cd45;
     set files.cd45;
     if case=6222 or case=6092 or case=6107 then delete; *excluding pilot data from analysis;
run;

PROC sort data = cd45;
     by case match_group hospbin age_group;
run;

PROC transpose data = cd45 out = cd45_no_insulin (rename =( a = Head b = Body c = Tail));
     by case match_group hospbin age_group;
     id sample_type2;
     var percent_cd45;
run;
Out[32]:

1141  ods listing close;ods html5 file=stdout options(bitmap_mode='inline') device=png; ods graphics on / outputfmt=png;
NOTE: Writing HTML5 Body file: STDOUT
1142
1143 DATA cd45;
1144 set files.cd45;
1145 if case=6222 or case=6092 or case=6107 then delete; *excluding pilot data from analysis;
1146 run;
NOTE: There were 126 observations read from the data set FILES.CD45.
NOTE: The data set WORK.CD45 has 117 observations and 20 variables.
NOTE: DATA statement used (Total process time):
real time 0.07 seconds
cpu time 0.00 seconds

1147
1148 PROC sort data = cd45;
1149 by case match_group hospbin age_group;
1150 run;
NOTE: There were 117 observations read from the data set WORK.CD45.
NOTE: The data set WORK.CD45 has 117 observations and 20 variables.
NOTE: PROCEDURE SORT used (Total process time):
real time 0.00 seconds
cpu time 0.01 seconds

1151
1152 PROC transpose data = cd45 out = cd45_no_insulin (rename =( a = Head b = Body c = Tail));
1153 by case match_group hospbin age_group;
1154 id sample_type2;
1155 var percent_cd45;
1156 run;
NOTE: There were 117 observations read from the data set WORK.CD45.
NOTE: The data set WORK.CD45_NO_INSULIN has 39 observations and 9 variables.
NOTE: PROCEDURE TRANSPOSE used (Total process time):
real time 0.01 seconds
cpu time 0.00 seconds

1157 ods html5 close;ods listing;

1158
In [33]:
PROC export data=cd45 
     outfile="cd45.csv" 
     dbms=csv
     replace;
run;
Out[33]:

1160  ods listing close;ods html5 file=stdout options(bitmap_mode='inline') device=png; ods graphics on / outputfmt=png;
NOTE: Writing HTML5 Body file: STDOUT
1161
1162 PROC export data=cd45
1163 outfile="cd45.csv"
1164 dbms=csv
1165 replace;
1166 run;
1167 /**********************************************************************
1168 * PRODUCT: SAS
1169 * VERSION: 9.4
1170 * CREATOR: External File Interface
1171 * DATE: 11SEP17
1172 * DESC: Generated SAS Datastep Code
1173 * TEMPLATE SOURCE: (None Specified.)
1174 ***********************************************************************/
1175 data _null_;
1176 %let _EFIERR_ = 0; /* set the ERROR detection macro variable */
1177 %let _EFIREC_ = 0; /* clear export record count macro variable */
1178 file 'cd45.csv' delimiter=',' DSD DROPOVER lrecl=32767;
1179 if _n_ = 1 then /* write column names or labels */
1180 do;
1181 put
1182 "Case"
1183 ','
1184 "hospbin"
1185 ','
1186 "Sample_Type"
1187 ','
1188 "Block__"
1189 ','
1190 "Staff"
1191 ','
1192 "classified_area"
1193 ','
1194 "__acinar___endocrine_Area"
1195 ','
1196 "__other_Area"
1197 ','
1198 "Total_Cells"
1199 ','
1200 "percent_insulin"
1201 ','
1202 "percent_cd45"
1203 ','
1204 "percent_negative"
1205 ','
1206 "tissue_area"
1207 ','
1208 "CD45_Case_Average"
1209 ','
1210 "O"
1211 ','
1212 "match_group"
1213 ','
1214 "oppc_ageR"
1215 ','
1216 "age_group"
1217 ','
1218 "sample_type1"
1219 ','
1220 "sample_type2"
1221 ;
1222 end;
1223 set CD45 end=EFIEOD;
1224 format Case best12. ;
1225 format hospbin best12. ;
1226 format Sample_Type $2. ;
1227 format Block__ $3. ;
1228 format Staff $2. ;
1229 format classified_area best12. ;
1230 format __acinar___endocrine_Area best12. ;
1231 format __other_Area best12. ;
1232 format Total_Cells best12. ;
1233 format percent_insulin best12. ;
1234 format percent_cd45 best12. ;
1235 format percent_negative best12. ;
1236 format tissue_area best12. ;
1237 format CD45_Case_Average comma15.3 ;
1238 format O $1. ;
1239 format match_group best12. ;
1240 format oppc_ageR best12. ;
1241 format age_group best12. ;
1242 format sample_type1 $2. ;
1243 format sample_type2 $1. ;
1244 do;
1245 EFIOUT + 1;
1246 put Case @;
1247 put hospbin @;
1248 put Sample_Type $ @;
1249 put Block__ $ @;
1250 put Staff $ @;
1251 put classified_area @;
1252 put __acinar___endocrine_Area @;
1253 put __other_Area @;
1254 put Total_Cells @;
1255 put percent_insulin @;
1256 put percent_cd45 @;
1257 put percent_negative @;
1258 put tissue_area @;
1259 put CD45_Case_Average @;
1260 put O $ @;
1261 put match_group @;
1262 put oppc_ageR @;
1263 put age_group @;
1264 put sample_type1 $ @;
1265 put sample_type2 $ ;
1266 ;
1267 end;
1268 if _ERROR_ then call symputx('_EFIERR_',1); /* set ERROR detection macro variable */
1269 if EFIEOD then call symputx('_EFIREC_',EFIOUT);
1270 run;
NOTE: The file 'cd45.csv' is:
Filename=/mnt/hgfs/myfolders/cd45.csv,
Owner Name=root,Group Name=vboxsf,
Access Permission=-rwxrwx---,
Last Modified=12Sep2017:19:33:09

NOTE: 118 records were written to the file 'cd45.csv'.
The minimum record length was 86.
The maximum record length was 241.
NOTE: There were 117 observations read from the data set WORK.CD45.
NOTE: DATA statement used (Total process time):
real time 0.04 seconds
cpu time 0.00 seconds

117 records created in cd45.csv from CD45.


NOTE: "cd45.csv" file was successfully created.
NOTE: PROCEDURE EXPORT used (Total process time):
real time 0.28 seconds
cpu time 0.04 seconds

1271 ods html5 close;ods listing;

1272

CD68 dataset

In [4]:
DATA cd68;
     set files.cd68;
     if case=6222 or case=6092 or case=6107 then delete; *excluding pilot data from analysis;
run;

PROC sort data = cd68;
     by case match_group hospbin age_group;
run;

PROC transpose data = cd68 out = cd68_no_insulin (rename=( a=Head b=Body c=Tail));
     by case match_group hospbin age_group;
     id sample_type2;
     var percent_CD68;
run;
Out[4]:

53   ods listing close;ods html5 file=stdout options(bitmap_mode='inline') device=png; ods graphics on / outputfmt=png;
NOTE: Writing HTML5 Body file: STDOUT
54
55 DATA cd68;
56 set files.cd68;
57 if case=6222 or case=6092 or case=6107 then delete; *excluding pilot data from analysis;
58 run;
NOTE: There were 126 observations read from the data set FILES.CD68.
NOTE: The data set WORK.CD68 has 117 observations and 23 variables.
NOTE: DATA statement used (Total process time):
real time 0.03 seconds
cpu time 0.00 seconds

59
60 PROC sort data = cd68;
61 by case match_group hospbin age_group;
62 run;
NOTE: There were 117 observations read from the data set WORK.CD68.
NOTE: The data set WORK.CD68 has 117 observations and 23 variables.
NOTE: PROCEDURE SORT used (Total process time):
real time 0.00 seconds
cpu time 0.00 seconds

63
64 PROC transpose data = cd68 out = cd68_no_insulin (rename=( a=Head b=Body c=Tail));
65 by case match_group hospbin age_group;
66 id sample_type2;
67 var percent_CD68;
68 run;
NOTE: There were 117 observations read from the data set WORK.CD68.
NOTE: The data set WORK.CD68_NO_INSULIN has 39 observations and 9 variables.
NOTE: PROCEDURE TRANSPOSE used (Total process time):
real time 0.00 seconds
cpu time 0.00 seconds

69 ods html5 close;ods listing;

70

Insulin dataset

In [5]:
DATA insulin;
     set files.insulin;
     if case=6222 or case=6092 or case=6107 then delete; *excluding pilot data from analysis;
run;

PROC sort data = insulin;
     by case match_group hospbin age_group;
run;

PROC transpose data = insulin out = insulin1 (rename =( a = Head b = Body c = Tail));
     by case match_group hospbin age_group;
     id sample_type2;
     var percent_insulin;
run;

proc PRINT data=insulin;
run;
Out[5]:
SAS Output

The SAS System

Obs Case sample_type2 hospbin match_group oppc_ageR age_group percent_insulin
1 6003 A 3 6 23 3 1.8283
2 6003 B 3 6 23 3 2.5740066667
3 6003 C 3 6 23 3 2.4044566667
4 6005 A 9 1 5 1 2.80085
5 6005 B 9 1 5 1 2.0971
6 6005 C 9 1 5 1 2.1478833333
7 6007 A 9 3 9 1 1.9701133333
8 6007 B 9 3 9 1 1.6219533333
9 6007 C 9 3 9 1 1.6327533333
10 6008 A 9 7 50 3 0.7234663333
11 6008 B 9 7 50 3 0.505701
12 6008 C 9 7 50 3 1.032517
13 6011 A 9 5 46 3 1.0369433333
14 6011 B 9 5 46 3 1.11986
15 6011 C 9 5 46 3 3.86339
16 6019 A 9 9 42 3 1.0779206667
17 6019 B 9 9 42 3 2.26666
18 6019 C 9 9 42 3 1.3961166667
19 6047 A 6 10 7.8 1 1.7823366667
20 6047 B 6 10 7.8 1 1.0935966667
21 6047 C 6 10 7.8 1 2.1224433333
22 6048 A 3 11 30 3 0.917634
23 6048 B 3 11 30 3 1.5497353333
24 6048 C 3 11 30 3 1.6243343333
25 6057 A 9 10 22 3 2.2846133333
26 6057 B 9 10 22 3 2.07547
27 6057 C 9 10 22 3 2.8383833333
28 6060 A 9 6 24 3 1.005877
29 6060 B 9 6 24 3 1.2035643333
30 6060 C 9 6 24 3 2.1855966667
31 6073 A 3 14 19.2 2 1.93746
32 6073 B 3 14 19.2 2 1.1759
33 6073 C 3 14 19.2 2 1.2178266667
34 6099 A 3 8 14.2 2 1.2174466667
35 6099 B 3 8 14.2 2 1.8557933333
36 6099 C 3 8 14.2 2 2.6249333333
37 6104 A 6 11 41 3 0.6244473333
38 6104 B 6 11 41 3 1.130861
39 6104 C 6 11 41 3 1.3389946667
40 6106 A 3 1 2.9 1 3.0632966667
41 6106 B 3 1 2.9 1 2.0135853333
42 6106 C 3 1 2.9 1 2.9010466667
43 6115 A 9 13 0.42 1 4.6895266667
44 6115 B 9 13 0.42 1 4.7205266667
45 6115 C 9 13 0.42 1 6.3141333333
46 6117 A 6 1 0.33 1 4.0546866667
47 6117 B 6 1 0.33 1 3.8187953333
48 6117 C 6 1 0.33 1 6.25566
49 6126 A 6 4 25.2 3 1.0027426667
50 6126 B 6 4 25.2 3 0.7686986667
51 6126 C 6 4 25.2 3 1.263569
52 6129 A 6 7 42.9 3 1.2439966667
53 6129 B 6 7 42.9 3 1.2644833333
54 6129 C 6 7 42.9 3 2.4633066667
55 6131 A 3 4 24.2 3 1.4713433333
56 6131 B 3 4 24.2 3 1.67022
57 6131 C 3 4 24.2 3 2.85991
58 6134 A 3 13 26.7 3 0.6421466667
59 6134 B 3 13 26.7 3 1.197635
60 6134 C 3 13 26.7 3 1.2266576667
61 6140 A 9 11 38 3 1.3909406667
62 6140 B 9 11 38 3 1.063971
63 6140 C 9 11 38 3 1.6712033333
64 6144 A 9 15 7.5 1 1.6490833333
65 6144 B 9 15 7.5 1 1.8886733333
66 6144 C 9 15 7.5 1 3.05935
67 6162 A 3 9 22.7 3 0.8367403333
68 6162 B 3 9 22.7 3 0.9931223333
69 6162 C 3 9 22.7 3 1.45839
70 6165 A 6 5 45.8 3 0.7183803333
71 6165 B 6 5 45.8 3 0.5528716667
72 6165 C 6 5 45.8 3 0.865764
73 6172 A 9 14 19.2 2 2.7757233333
74 6172 B 9 14 19.2 2 2.45087
75 6172 C 9 14 19.2 2 2.8240766667
76 6174 A 3 3 20.8 3 1.4925566667
77 6174 B 3 3 20.8 3 0.9973946667
78 6174 C 3 3 20.8 3 1.7100066667
79 6178 A 9 8 24.5 3 1.43543
80 6178 B 9 8 24.5 3 0.579835
81 6178 C 9 8 24.5 3 1.709
82 6179 A 9 4 21.8 3 0.8361326667
83 6179 B 9 4 21.8 3 0.6573286667
84 6179 C 9 4 21.8 3 1.1253213333
85 6187 A 6 13 0.33 1 8.3023366667
86 6187 B 6 13 0.33 1 8.1725033333
87 6187 C 6 13 0.33 1 9.5139033333
88 6200 A 3 15 0.0065753425 1 18.724866667
89 6200 B 3 15 0.0065753425 1 13.30311
90 6200 C 3 15 0.0065753425 1 14.342366667
91 6219 A 6 15 0.5 1 5.68479
92 6219 B 6 15 0.5 1 3.84164
93 6219 C 6 15 0.5 1 3.0985266667
94 6229 A 6 8 31 3 2.2153966667
95 6229 B 6 8 31 3 3.0677333333
96 6229 C 6 8 31 3 4.2785833333
97 6230 A 6 3 16 2 1.1613076667
98 6230 B 6 3 16 2 0.6409103333
99 6230 C 6 3 16 2 1.153724
100 6235 A 3 7 30 3 1.1162433333
101 6235 B 3 7 30 3 0.8294196667
102 6235 C 3 7 30 3 1.0368146667
103 6250 A 3 5 40 3 2.08171
104 6250 B 3 5 40 3 1.2777566667
105 6250 C 3 5 40 3 2.07871
106 6251 A 6 6 33 3 0.887811
107 6251 B 6 6 33 3 1.015094
108 6251 C 6 6 33 3 1.2318556667
109 6254 A 6 9 38 3 1.5299233333
110 6254 B 6 9 38 3 1.4146366667
111 6254 C 6 9 38 3 2.4829633333
112 6278 A 3 10 10 1 2.6689533333
113 6278 B 3 10 10 1 2.7352133333
114 6278 C 3 10 10 1 3.4812766667
115 6279 A 6 14 19 2 2.1495866667
116 6279 B 6 14 19 2 1.6337966667
117 6279 C 6 14 19 2 3.5184733333

Need to export data for ESM Figure 2 generation

In [6]:
PROC export data=insulin 
     outfile="insulin.csv" 
     dbms=csv
     replace;
run;
Out[6]:

94   ods listing close;ods html5 file=stdout options(bitmap_mode='inline') device=png; ods graphics on / outputfmt=png;
NOTE: Writing HTML5 Body file: STDOUT
95
96 PROC export data=insulin
97 outfile="insulin.csv"
98 dbms=csv
99 replace;
100 run;
ERROR: Expecting page 1, got page -1 instead.
ERROR: Page validation error while reading SASUSER.PROFILE.CATALOG.
NOTE: Unable to open SASUSER.PROFILE. WORK.PROFILE will be opened instead.
NOTE: All profile changes will be lost at the end of the session.
101 /**********************************************************************
102 * PRODUCT: SAS
103 * VERSION: 9.4
104 * CREATOR: External File Interface
105 * DATE: 11SEP17
106 * DESC: Generated SAS Datastep Code
107 * TEMPLATE SOURCE: (None Specified.)
108 ***********************************************************************/
109 data _null_;
110 %let _EFIERR_ = 0; /* set the ERROR detection macro variable */
111 %let _EFIREC_ = 0; /* clear export record count macro variable */
112 file 'insulin.csv' delimiter=',' DSD DROPOVER lrecl=32767;
113 if _n_ = 1 then /* write column names or labels */
114 do;
115 put
116 "Case"
117 ','
118 "sample_type2"
119 ','
120 "hospbin"
121 ','
122 "match_group"
123 ','
124 "oppc_ageR"
125 ','
126 "age_group"
127 ','
128 "percent_insulin"
129 ;
130 end;
131 set INSULIN end=EFIEOD;
132 format Case best12. ;
133 format sample_type2 $1. ;
134 format hospbin best12. ;
135 format match_group best12. ;
136 format oppc_ageR best12. ;
137 format age_group best12. ;
138 format percent_insulin best12. ;
139 do;
140 EFIOUT + 1;
141 put Case @;
142 put sample_type2 $ @;
143 put hospbin @;
144 put match_group @;
145 put oppc_ageR @;
146 put age_group @;
147 put percent_insulin ;
148 ;
149 end;
150 if _ERROR_ then call symputx('_EFIERR_',1); /* set ERROR detection macro variable */
151 if EFIEOD then call symputx('_EFIREC_',EFIOUT);
152 run;
NOTE: The file 'insulin.csv' is:
Filename=/mnt/hgfs/myfolders/insulin.csv,
Owner Name=root,Group Name=vboxsf,
Access Permission=-rwxrwx---,
Last Modified=11Sep2017:22:25:07

NOTE: 118 records were written to the file 'insulin.csv'.
The minimum record length was 21.
The maximum record length was 73.
NOTE: There were 117 observations read from the data set WORK.INSULIN.
NOTE: DATA statement used (Total process time):
real time 0.04 seconds
cpu time 0.00 seconds

117 records created in insulin.csv from INSULIN.


NOTE: "insulin.csv" file was successfully created.
NOTE: PROCEDURE EXPORT used (Total process time):
real time 0.37 seconds
cpu time 0.06 seconds

153 ods html5 close;ods listing;

154

Ki67 dataset

In [7]:
DATA ki67;
     set files.ki67;
     if case=6222 or case=6092 or case=6107 then delete; *excluding pilot data from analysis;
run;

PROC sort data = ki67;
     by case match_group hospbin age_group;
run;

PROC transpose data = ki67 out = ki67_no_insulin (rename = (a = Head b = Body c = Tail));
     by case match_group hospbin age_group;
     id sample_type2;
     var percent_ki67;
run;  

PROC transpose data = ki67 out = ki67_dual (rename = (a = Head b = Body c = Tail));
     by case match_group hospbin age_group;
     id sample_type2;
     var percent_dual;
run; 
Out[7]:

156  ods listing close;ods html5 file=stdout options(bitmap_mode='inline') device=png; ods graphics on / outputfmt=png;
NOTE: Writing HTML5 Body file: STDOUT
157
158 DATA ki67;
159 set files.ki67;
160 if case=6222 or case=6092 or case=6107 then delete; *excluding pilot data from analysis;
161 run;
NOTE: There were 126 observations read from the data set FILES.KI67.
NOTE: The data set WORK.KI67 has 117 observations and 22 variables.
NOTE: DATA statement used (Total process time):
real time 0.03 seconds
cpu time 0.00 seconds

162
163 PROC sort data = ki67;
164 by case match_group hospbin age_group;
165 run;
NOTE: There were 117 observations read from the data set WORK.KI67.
NOTE: The data set WORK.KI67 has 117 observations and 22 variables.
NOTE: PROCEDURE SORT used (Total process time):
real time 0.00 seconds
cpu time 0.00 seconds

166
167 PROC transpose data = ki67 out = ki67_no_insulin (rename = (a = Head b = Body c = Tail));
168 by case match_group hospbin age_group;
169 id sample_type2;
170 var percent_ki67;
171 run;
NOTE: There were 117 observations read from the data set WORK.KI67.
NOTE: The data set WORK.KI67_NO_INSULIN has 39 observations and 9 variables.
NOTE: PROCEDURE TRANSPOSE used (Total process time):
real time 0.00 seconds
cpu time 0.01 seconds

172
173 PROC transpose data = ki67 out = ki67_dual (rename = (a = Head b = Body c = Tail));
174 by case match_group hospbin age_group;
175 id sample_type2;
176 var percent_dual;
177 run;
NOTE: There were 117 observations read from the data set WORK.KI67.
NOTE: The data set WORK.KI67_DUAL has 39 observations and 9 variables.
NOTE: PROCEDURE TRANSPOSE used (Total process time):
real time 0.00 seconds
cpu time 0.00 seconds

178 ods html5 close;ods listing;

179

Need to export data for ESM Figure 3 generation

In [8]:
PROC export data=ki67 
     outfile="ki67.csv" 
     dbms=csv

replace;
run;
Out[8]:

181  ods listing close;ods html5 file=stdout options(bitmap_mode='inline') device=png; ods graphics on / outputfmt=png;
NOTE: Writing HTML5 Body file: STDOUT
182
183 PROC export data=ki67
184 outfile="ki67.csv"
185 dbms=csv
186 replace;
187 run;
188 /**********************************************************************
189 * PRODUCT: SAS
190 * VERSION: 9.4
191 * CREATOR: External File Interface
192 * DATE: 11SEP17
193 * DESC: Generated SAS Datastep Code
194 * TEMPLATE SOURCE: (None Specified.)
195 ***********************************************************************/
196 data _null_;
197 %let _EFIERR_ = 0; /* set the ERROR detection macro variable */
198 %let _EFIREC_ = 0; /* clear export record count macro variable */
199 file 'ki67.csv' delimiter=',' DSD DROPOVER lrecl=32767;
200 if _n_ = 1 then /* write column names or labels */
201 do;
202 put
203 "Case"
204 ','
205 "hospbin"
206 ','
207 "Sample_Type"
208 ','
209 "Block__"
210 ','
211 "Staff"
212 ','
213 "classified_area"
214 ','
215 "__acinar__endocrine_Area"
216 ','
217 "__other_Area"
218 ','
219 "Total_Cells"
220 ','
221 "percent_insulin"
222 ','
223 "percent_ki67"
224 ','
225 "percent_dual"
226 ','
227 "percent_negative"
228 ','
229 "tissue_area"
230 ','
231 "Ki67_Case_Average"
232 ','
233 "Ki67_Dual_Positive_Case_Average"
234 ','
235 "Q"
236 ','
237 "match_group"
238 ','
239 "oppc_ageR"
240 ','
241 "age_group"
242 ','
243 "sample_type1"
244 ','
245 "sample_type2"
246 ;
247 end;
248 set KI67 end=EFIEOD;
249 format Case best12. ;
250 format hospbin best12. ;
251 format Sample_Type $2. ;
252 format Block__ $3. ;
253 format Staff $6. ;
254 format classified_area comma15.5 ;
255 format __acinar__endocrine_Area best12. ;
256 format __other_Area best12. ;
257 format Total_Cells best12. ;
258 format percent_insulin best12. ;
259 format percent_ki67 comma15.5 ;
260 format percent_dual comma15.7 ;
261 format percent_negative best12. ;
262 format tissue_area best12. ;
263 format Ki67_Case_Average comma15.3 ;
264 format Ki67_Dual_Positive_Case_Average comma15.3 ;
265 format Q $1. ;
266 format match_group best12. ;
267 format oppc_ageR best12. ;
268 format age_group best12. ;
269 format sample_type1 $2. ;
270 format sample_type2 $1. ;
271 do;
272 EFIOUT + 1;
273 put Case @;
274 put hospbin @;
275 put Sample_Type $ @;
276 put Block__ $ @;
277 put Staff $ @;
278 put classified_area @;
279 put __acinar__endocrine_Area @;
280 put __other_Area @;
281 put Total_Cells @;
282 put percent_insulin @;
283 put percent_ki67 @;
284 put percent_dual @;
285 put percent_negative @;
286 put tissue_area @;
287 put Ki67_Case_Average @;
288 put Ki67_Dual_Positive_Case_Average @;
289 put Q $ @;
290 put match_group @;
291 put oppc_ageR @;
292 put age_group @;
293 put sample_type1 $ @;
294 put sample_type2 $ ;
295 ;
296 end;
297 if _ERROR_ then call symputx('_EFIERR_',1); /* set ERROR detection macro variable */
298 if EFIEOD then call symputx('_EFIREC_',EFIOUT);
299 run;
NOTE: The file 'ki67.csv' is:
Filename=/mnt/hgfs/myfolders/ki67.csv,
Owner Name=root,Group Name=vboxsf,
Access Permission=-rwxrwx---,
Last Modified=11Sep2017:22:25:08

NOTE: 118 records were written to the file 'ki67.csv'.
The minimum record length was 96.
The maximum record length was 285.
NOTE: There were 117 observations read from the data set WORK.KI67.
NOTE: DATA statement used (Total process time):
real time 0.03 seconds
cpu time 0.01 seconds

117 records created in ki67.csv from KI67.


NOTE: "ki67.csv" file was successfully created.
NOTE: PROCEDURE EXPORT used (Total process time):
real time 0.28 seconds
cpu time 0.04 seconds

300 ods html5 close;ods listing;

301

Statistical Testing

See main text for details. In brief, p-values from univariate between subjects effects testing are used directly, since it is not reliant upon the Huynh-Feldt (HF) condition being met. p-values for within subjects effects testing are determined by first checking for sphericity. If orthogonal components significant, greenhouse-geisser p-values from univariate within subjects effects table are used. Otherwise, unadjusted univariate p-values were used for both between and within subjects effects, including the interaction term.

In [9]:
/*6 = '^{unicode 2265}3 to 6 days'  something to do with unicode */
PROC format;
     value $pancorder
     'A' = 'Head'
     'B' = 'Body'
     'C' = 'Tail';
     value hospname
     3 = "<3                             "
     6 = "(*ESC*){unicode '2265'x}3, <6"
     9 = "(*ESC*){unicode '2265'x}6      ";
     value agename
     1 = "<12                              "
     2 = "(*ESC*){unicode '2265'x}12, <20"
     3 = "(*ESC*){unicode '2265'x}20       ";
run;
Out[9]:

303  ods listing close;ods html5 file=stdout options(bitmap_mode='inline') device=png; ods graphics on / outputfmt=png;
NOTE: Writing HTML5 Body file: STDOUT
304
305 /*6 = '^{unicode 2265}3 to 6 days' something to do with unicode */
306 PROC format;
307 value $pancorder
308 'A' = 'Head'
309 'B' = 'Body'
NOTE: Format $PANCORDER has been output.
310 'C' = 'Tail';
311 value hospname
312 3 = "<3 "
313 6 = "(*ESC*){unicode '2265'x}3, <6"
NOTE: Format HOSPNAME has been output.
314 9 = "(*ESC*){unicode '2265'x}6 ";
315 value agename
316 1 = "<12 "
317 2 = "(*ESC*){unicode '2265'x}12, <20"
NOTE: Format AGENAME has been output.
318 3 = "(*ESC*){unicode '2265'x}20 ";
319 run;
NOTE: PROCEDURE FORMAT used (Total process time):
real time 0.02 seconds
cpu time 0.01 seconds

320 ods html5 close;ods listing;

321

CD45 dataset

Statistical analysis model

In [10]:
/*to perform sphericity tests and model p-values*/

PROC glm data=cd45_no_insulin;
     class hospbin age_group;
     model Head Body Tail= hospbin|age_group /nouni; 
         *nouni to suppress display of univariate stats;
         *solution not used to display parameter estimates;
         *clparm not used to display confidence limits for parameter estimates;
     repeated sample_type2 / short printe; 
         *short for abbreviated version of output;
         *printe provides e matrix, sphericity tests, partial correlations;
     lsmeans hospbin|age_group / out=cd45_lsmeans (drop=stderr);
run;
quit;



/*to obtain all LSmeans and SE values, perform individual comparisons, retrieve differences and assoc. confidence intervals*/
ods output diffs=cd45_lsmeans_diff;

PROC mixed data=cd45;
     class case hospbin age_group sample_type2;
     model percent_cd45=hospbin|age_group|sample_type2;
     repeated sample_type2/ subject=case(hospbin) type=un;
     lsmeans hospbin|age_group|sample_type2 /adjust=tukey cl pdiff alpha=0.05;
run;

ods output close;
Out[10]:
SAS Output

The SAS System

The GLM Procedure

Class Level Information
Class Levels Values
hospbin 3 3 6 9
age_group 3 1 2 3
Number of Observations Read 39
Number of Observations Used 39

The SAS System

The GLM Procedure

Repeated Measures Analysis of Variance

Repeated Measures Level Information
Dependent Variable Head Body Tail
Level of sample_type2 1 2 3
Partial Correlation Coefficients from the Error SSCP Matrix / Prob > |r|
DF = 30 Head Body Tail
Head
1.000000
 
0.853941
<.0001
0.899225
<.0001
Body
0.853941
<.0001
1.000000
 
0.945839
<.0001
Tail
0.899225
<.0001
0.945839
<.0001
1.000000
 
E = Error SSCP Matrix

sample_type2_N represents the contrast between the nth level of sample_type2 and the last
  sample_type2_1 sample_type2_2
sample_type2_1 144.436 61.872
sample_type2_2 61.872 80.400
Partial Correlation Coefficients from the Error SSCP Matrix of the Variables Defined by the Specified Transformation / Prob > |r|
DF = 30 sample_type2_1 sample_type2_2
sample_type2_1
1.000000
 
0.574155
0.0007
sample_type2_2
0.574155
0.0007
1.000000
 
Sphericity Tests
Variables DF Mauchly's Criterion Chi-Square Pr > ChiSq
Transformed Variates 2 0.6159692 14.052192 0.0009
Orthogonal Components 2 0.8793648 3.7281087 0.1550
MANOVA Test Criteria and Exact F Statistics for the Hypothesis of no sample_type2 Effect
H = Type III SSCP Matrix for sample_type2
E = Error SSCP Matrix

S=1 M=0 N=13.5
Statistic Value F Value Num DF Den DF Pr > F
Wilks' Lambda 0.77164509 4.29 2 29 0.0233
Pillai's Trace 0.22835491 4.29 2 29 0.0233
Hotelling-Lawley Trace 0.29593257 4.29 2 29 0.0233
Roy's Greatest Root 0.29593257 4.29 2 29 0.0233
MANOVA Test Criteria and F Approximations for the Hypothesis of no sample_type2*hospbin Effect
H = Type III SSCP Matrix for sample_type2*hospbin
E = Error SSCP Matrix

S=2 M=-0.5 N=13.5
Statistic Value F Value Num DF Den DF Pr > F
NOTE: F Statistic for Roy's Greatest Root is an upper bound.
NOTE: F Statistic for Wilks' Lambda is exact.
Wilks' Lambda 0.95826634 0.31 4 58 0.8686
Pillai's Trace 0.04202564 0.32 4 60 0.8622
Hotelling-Lawley Trace 0.04324652 0.31 4 33.787 0.8691
Roy's Greatest Root 0.03438543 0.52 2 30 0.6022
MANOVA Test Criteria and F Approximations for the Hypothesis of no sample_type2*age_group Effect
H = Type III SSCP Matrix for sample_type2*age_group
E = Error SSCP Matrix

S=2 M=-0.5 N=13.5
Statistic Value F Value Num DF Den DF Pr > F
NOTE: F Statistic for Roy's Greatest Root is an upper bound.
NOTE: F Statistic for Wilks' Lambda is exact.
Wilks' Lambda 0.82215686 1.49 4 58 0.2166
Pillai's Trace 0.18300948 1.51 4 60 0.2104
Hotelling-Lawley Trace 0.21002904 1.51 4 33.787 0.2222
Roy's Greatest Root 0.17389247 2.61 2 30 0.0903
MANOVA Test Criteria and F Approximations for the Hypothesis of no sample_type2*hospbin*age_group Effect
H = Type III SSCP Matrix for sample_type2*hospbin*age_group
E = Error SSCP Matrix

S=2 M=0.5 N=13.5
Statistic Value F Value Num DF Den DF Pr > F
NOTE: F Statistic for Roy's Greatest Root is an upper bound.
NOTE: F Statistic for Wilks' Lambda is exact.
Wilks' Lambda 0.77878419 0.97 8 58 0.4718
Pillai's Trace 0.23077470 0.98 8 60 0.4617
Hotelling-Lawley Trace 0.27177865 0.97 8 39.176 0.4757
Roy's Greatest Root 0.21457726 1.61 4 30 0.1977

The SAS System

The GLM Procedure

Repeated Measures Analysis of Variance

Tests of Hypotheses for Between Subjects Effects

Source DF Type III SS Mean Square F Value Pr > F
hospbin 2 9.095703 4.547852 0.12 0.8893
age_group 2 38.711772 19.355886 0.50 0.6107
hospbin*age_group 4 107.437759 26.859440 0.70 0.6009
Error 30 1158.413425 38.613781    

The SAS System

The GLM Procedure

Repeated Measures Analysis of Variance

Univariate Tests of Hypotheses for Within Subject Effects

Source DF Type III SS Mean Square F Value Pr > F Adj Pr > F
G - G H-F-L
sample_type2 2 16.9601417 8.4800709 4.68 0.0129 0.0163 0.0145
sample_type2*hospbin 4 1.8938107 0.4734527 0.26 0.9015 0.8833 0.8926
sample_type2*age_group 4 13.7670183 3.4417546 1.90 0.1220 0.1307 0.1264
sample_type2*hospbin*age_group 8 16.1038820 2.0129853 1.11 0.3684 0.3696 0.3691
Error(sample_type2) 60 108.6423203 1.8107053        
Greenhouse-Geisser Epsilon 0.8924
Huynh-Feldt-Lecoutre Epsilon 0.9450

The SAS System

The GLM Procedure

Least Squares Means

hospbin Head LSMEAN
3 3.97633139
6 3.64361595
9 4.86435500
Plot of Head least-squares means for hospbin.
hospbin Body LSMEAN
3 4.21742319
6 4.17155869
9 4.61384008
Plot of Body least-squares means for hospbin.
hospbin Tail LSMEAN
3 5.35137056
6 4.70966214
9 5.66879708
Plot of Tail least-squares means for hospbin.
age_group Head LSMEAN
1 4.49802806
2 3.47979117
3 4.50648312
Plot of Head least-squares means for age_group.
age_group Body LSMEAN
1 4.37508161
2 3.28959667
3 5.33814369
Plot of Body least-squares means for age_group.
age_group Tail LSMEAN
1 4.55677139
2 4.76605417
3 6.40700423
Plot of Tail least-squares means for age_group.
hospbin age_group Head LSMEAN
3 1 3.46834667
3 2 5.05541500
3 3 3.40523250
6 1 4.36122750
6 2 2.08444850
6 3 4.48517186
9 1 5.66451000
9 2 3.29951000
9 3 5.62904500
Plot of Head least-squares means for hospbin*age_group.
hospbin age_group Body LSMEAN
3 1 3.52531333
3 2 5.50029000
3 3 3.62666625
6 1 4.99802750
6 2 1.68586000
6 3 5.83078857
9 1 4.60190400
9 2 2.68264000
9 3 6.55697625
Plot of Body least-squares means for hospbin*age_group.
hospbin age_group Tail LSMEAN
3 1 4.18222667
3 2 7.61160000
3 3 4.26028500
6 1 4.56364250
6 2 1.84092250
6 3 7.72442143
9 1 4.92444500
9 2 4.84564000
9 3 7.23630625
Plot of Tail least-squares means for hospbin*age_group.

The SAS System

The Mixed Procedure

Model Information
Data Set WORK.CD45
Dependent Variable percent_cd45
Covariance Structure Unstructured
Subject Effect Case(hospbin)
Estimation Method REML
Residual Variance Method None
Fixed Effects SE Method Model-Based
Degrees of Freedom Method Between-Within
Class Level Information
Class Levels Values
Case 39 6003 6005 6007 6008 6011 6019 6047 6048 6057 6060 6073 6099 6104 6106 6115 6117 6126 6129 6131 6134 6140 6144 6162 6165 6172 6174 6178 6179 6187 6200 6219 6229 6230 6235 6250 6251 6254 6278 6279
hospbin 3 3 6 9
age_group 3 1 2 3
sample_type2 3 A B C
Dimensions
Covariance Parameters 6
Columns in X 64
Columns in Z 0
Subjects 39
Max Obs per Subject 3
Number of Observations
Number of Observations Read 117
Number of Observations Used 117
Number of Observations Not Used 0
Iteration History
Iteration Evaluations -2 Res Log Like Criterion
0 1 527.51353740  
1 1 405.87052007 0.00000000
Convergence criteria met.
Covariance Parameter Estimates
Cov Parm Subject Estimate
UN(1,1) Case(hospbin) 9.5215
UN(2,1) Case(hospbin) 9.2874
UN(2,2) Case(hospbin) 12.4230
UN(3,1) Case(hospbin) 12.4988
UN(3,2) Case(hospbin) 15.0169
UN(3,3) Case(hospbin) 20.2907
Fit Statistics
-2 Res Log Likelihood 405.9
AIC (Smaller is Better) 417.9
AICC (Smaller is Better) 418.9
BIC (Smaller is Better) 427.9
Null Model Likelihood Ratio Test
DF Chi-Square Pr > ChiSq
5 121.64 <.0001
Type 3 Tests of Fixed Effects
Effect Num DF Den DF F Value Pr > F
hospbin 2 30 0.12 0.8893
age_group 2 30 0.50 0.6107
hospbin*age_group 4 30 0.70 0.6009
sample_type2 2 30 4.44 0.0205
hospbin*sample_type2 4 30 0.32 0.8594
age_group*sample_typ 4 30 1.58 0.2064
hospbi*age_gr*sample 8 30 1.02 0.4432
Least Squares Means
Effect sample_type2 hospbin age_group Estimate Standard
Error
DF t Value Pr > |t| Alpha Lower Upper
hospbin   3   4.5150 1.1707 30 3.86 0.0006 0.05 2.1241 6.9059
hospbin   6   4.1749 1.1300 30 3.69 0.0009 0.05 1.8672 6.4827
hospbin   9   5.0490 1.4023 30 3.60 0.0011 0.05 2.1851 7.9129
age_group     1 4.4766 1.0917 30 4.10 0.0003 0.05 2.2471 6.7062
age_group     2 3.8451 1.6912 30 2.27 0.0303 0.05 0.3912 7.2991
age_group     3 5.4172 0.7496 30 7.23 <.0001 0.05 3.8864 6.9480
hospbin*age_group   3 1 3.7253 2.0713 30 1.80 0.0822 0.05 -0.5049 7.9555
hospbin*age_group   3 2 6.0558 2.5369 30 2.39 0.0235 0.05 0.8748 11.2367
hospbin*age_group   3 3 3.7641 1.2684 30 2.97 0.0058 0.05 1.1736 6.3545
hospbin*age_group   6 1 4.6410 1.7938 30 2.59 0.0148 0.05 0.9775 8.3044
hospbin*age_group   6 2 1.8704 2.5369 30 0.74 0.4667 0.05 -3.3105 7.0514
hospbin*age_group   6 3 6.0135 1.3560 30 4.43 0.0001 0.05 3.2441 8.7828
hospbin*age_group   9 1 5.0636 1.7938 30 2.82 0.0084 0.05 1.4001 8.7271
hospbin*age_group   9 2 3.6093 3.5877 30 1.01 0.3225 0.05 -3.7177 10.9362
hospbin*age_group   9 3 6.4741 1.2684 30 5.10 <.0001 0.05 3.8836 9.0646
sample_type2 A     4.1614 0.6158 30 6.76 <.0001 0.05 2.9038 5.4191
sample_type2 B     4.3343 0.7034 30 6.16 <.0001 0.05 2.8977 5.7709
sample_type2 C     5.2433 0.8990 30 5.83 <.0001 0.05 3.4073 7.0792
hospbin*sample_type2 A 3   3.9763 1.0069 30 3.95 0.0004 0.05 1.9200 6.0327
hospbin*sample_type2 B 3   4.2174 1.1501 30 3.67 0.0009 0.05 1.8685 6.5663
hospbin*sample_type2 C 3   5.3514 1.4699 30 3.64 0.0010 0.05 2.3494 8.3533
hospbin*sample_type2 A 6   3.6436 0.9719 30 3.75 0.0008 0.05 1.6587 5.6285
hospbin*sample_type2 B 6   4.1716 1.1102 30 3.76 0.0007 0.05 1.9043 6.4388
hospbin*sample_type2 C 6   4.7097 1.4188 30 3.32 0.0024 0.05 1.8121 7.6072
hospbin*sample_type2 A 9   4.8644 1.2061 30 4.03 0.0003 0.05 2.4012 7.3275
hospbin*sample_type2 B 9   4.6138 1.3777 30 3.35 0.0022 0.05 1.8003 7.4274
hospbin*sample_type2 C 9   5.6688 1.7607 30 3.22 0.0031 0.05 2.0730 9.2646
age_group*sample_typ A   1 4.4980 0.9389 30 4.79 <.0001 0.05 2.5804 6.4156
age_group*sample_typ B   1 4.3751 1.0725 30 4.08 0.0003 0.05 2.1847 6.5654
age_group*sample_typ C   1 4.5568 1.3707 30 3.32 0.0023 0.05 1.7575 7.3561
age_group*sample_typ A   2 3.4798 1.4546 30 2.39 0.0232 0.05 0.5091 6.4505
age_group*sample_typ B   2 3.2896 1.6615 30 1.98 0.0570 0.05 -0.1037 6.6829
age_group*sample_typ C   2 4.7661 2.1235 30 2.24 0.0323 0.05 0.4294 9.1027
age_group*sample_typ A   3 4.5065 0.6447 30 6.99 <.0001 0.05 3.1899 5.8231
age_group*sample_typ B   3 5.3381 0.7364 30 7.25 <.0001 0.05 3.8342 6.8421
age_group*sample_typ C   3 6.4070 0.9411 30 6.81 <.0001 0.05 4.4850 8.3290
hospbi*age_gr*sample A 3 1 3.4683 1.7815 30 1.95 0.0610 0.05 -0.1700 7.1067
hospbi*age_gr*sample B 3 1 3.5253 2.0349 30 1.73 0.0935 0.05 -0.6306 7.6812
hospbi*age_gr*sample C 3 1 4.1822 2.6007 30 1.61 0.1183 0.05 -1.1291 9.4935
hospbi*age_gr*sample A 3 2 5.0554 2.1819 30 2.32 0.0275 0.05 0.5994 9.5115
hospbi*age_gr*sample B 3 2 5.5003 2.4923 30 2.21 0.0351 0.05 0.4104 10.5902
hospbi*age_gr*sample C 3 2 7.6116 3.1852 30 2.39 0.0233 0.05 1.1066 14.1166
hospbi*age_gr*sample A 3 3 3.4052 1.0910 30 3.12 0.0040 0.05 1.1772 5.6333
hospbi*age_gr*sample B 3 3 3.6267 1.2461 30 2.91 0.0067 0.05 1.0817 6.1716
hospbi*age_gr*sample C 3 3 4.2603 1.5926 30 2.68 0.0120 0.05 1.0078 7.5128
hospbi*age_gr*sample A 6 1 4.3612 1.5428 30 2.83 0.0083 0.05 1.2103 7.5121
hospbi*age_gr*sample B 6 1 4.9980 1.7623 30 2.84 0.0081 0.05 1.3989 8.5972
hospbi*age_gr*sample C 6 1 4.5636 2.2523 30 2.03 0.0517 0.05 -0.03609 9.1634
hospbi*age_gr*sample A 6 2 2.0844 2.1819 30 0.96 0.3470 0.05 -2.3716 6.5405
hospbi*age_gr*sample B 6 2 1.6859 2.4923 30 0.68 0.5039 0.05 -3.4041 6.7758
hospbi*age_gr*sample C 6 2 1.8409 3.1852 30 0.58 0.5676 0.05 -4.6641 8.3459
hospbi*age_gr*sample A 6 3 4.4852 1.1663 30 3.85 0.0006 0.05 2.1033 6.8670
hospbi*age_gr*sample B 6 3 5.8308 1.3322 30 4.38 0.0001 0.05 3.1101 8.5515
hospbi*age_gr*sample C 6 3 7.7244 1.7025 30 4.54 <.0001 0.05 4.2474 11.2015
hospbi*age_gr*sample A 9 1 5.6645 1.5428 30 3.67 0.0009 0.05 2.5136 8.8154
hospbi*age_gr*sample B 9 1 4.6019 1.7623 30 2.61 0.0139 0.05 1.0028 8.2010
hospbi*age_gr*sample C 9 1 4.9244 2.2523 30 2.19 0.0367 0.05 0.3247 9.5242
hospbi*age_gr*sample A 9 2 3.2995 3.0857 30 1.07 0.2935 0.05 -3.0023 9.6013
hospbi*age_gr*sample B 9 2 2.6826 3.5246 30 0.76 0.4525 0.05 -4.5156 9.8809
hospbi*age_gr*sample C 9 2 4.8456 4.5045 30 1.08 0.2906 0.05 -4.3538 14.0451
hospbi*age_gr*sample A 9 3 5.6290 1.0910 30 5.16 <.0001 0.05 3.4010 7.8571
hospbi*age_gr*sample B 9 3 6.5570 1.2461 30 5.26 <.0001 0.05 4.0120 9.1019
hospbi*age_gr*sample C 9 3 7.2363 1.5926 30 4.54 <.0001 0.05 3.9838 10.4888
Differences of Least Squares Means
Effect sample_type2 hospbin age_group _sample_type2 hospbin _age_group Estimate Standard
Error
DF t Value Pr > |t| Adjustment Adj P Alpha Lower Upper Adj Lower Adj Upper
hospbin   3     6   0.3401 1.6271 30 0.21 0.8358 Tukey-Kramer 0.9762 0.05 -2.9829 3.6631 -3.6711 4.3513
hospbin   3     9   -0.5340 1.8267 30 -0.29 0.7721 Tukey-Kramer 0.9541 0.05 -4.2647 3.1968 -5.0373 3.9694
hospbin   6     9   -0.8741 1.8009 30 -0.49 0.6310 Tukey-Kramer 0.8788 0.05 -4.5520 2.8039 -5.3138 3.5657
age_group     1     2 0.6315 2.0130 30 0.31 0.7559 Tukey-Kramer 0.9473 0.05 -3.4796 4.7425 -4.3310 5.5940
age_group     1     3 -0.9406 1.3242 30 -0.71 0.4830 Tukey-Kramer 0.7593 0.05 -3.6451 1.7639 -4.2052 2.3240
age_group     2     3 -1.5721 1.8499 30 -0.85 0.4022 Tukey-Kramer 0.6755 0.05 -5.3501 2.2059 -6.1325 2.9884
hospbin*age_group   3 1   3 2 -2.3305 3.2751 30 -0.71 0.4822 Tukey-Kramer 0.9982 0.05 -9.0190 4.3581 -13.2610 8.6001
hospbin*age_group   3 1   3 3 -0.03877 2.4289 30 -0.02 0.9874 Tukey-Kramer 1.0000 0.05 -4.9991 4.9216 -8.1451 8.0675
hospbin*age_group   3 1   6 1 -0.9157 2.7401 30 -0.33 0.7406 Tukey-Kramer 1.0000 0.05 -6.5117 4.6804 -10.0608 8.2295
hospbin*age_group   3 1   6 2 1.8549 3.2751 30 0.57 0.5754 Tukey-Kramer 0.9997 0.05 -4.8337 8.5435 -9.0756 12.7854
hospbin*age_group   3 1   6 3 -2.2882 2.4757 30 -0.92 0.3627 Tukey-Kramer 0.9896 0.05 -7.3443 2.7679 -10.5509 5.9745
hospbin*age_group   3 1   9 1 -1.3383 2.7401 30 -0.49 0.6288 Tukey-Kramer 0.9999 0.05 -6.9344 4.2577 -10.4835 7.8068
hospbin*age_group   3 1   9 2 0.1160 4.1427 30 0.03 0.9778 Tukey-Kramer 1.0000 0.05 -8.3444 8.5765 -13.7101 13.9422
hospbin*age_group   3 1   9 3 -2.7488 2.4289 30 -1.13 0.2667 Tukey-Kramer 0.9643 0.05 -7.7092 2.2116 -10.8551 5.3575
hospbin*age_group   3 2   3 3 2.2917 2.8363 30 0.81 0.4255 Tukey-Kramer 0.9957 0.05 -3.5008 8.0842 -7.1744 11.7578
hospbin*age_group   3 2   6 1 1.4148 3.1070 30 0.46 0.6521 Tukey-Kramer 0.9999 0.05 -4.9305 7.7601 -8.9548 11.7844
hospbin*age_group   3 2   6 2 4.1854 3.5877 30 1.17 0.2526 Tukey-Kramer 0.9575 0.05 -3.1416 11.5123 -7.7884 16.1592
hospbin*age_group   3 2   6 3 0.04231 2.8765 30 0.01 0.9884 Tukey-Kramer 1.0000 0.05 -5.8323 5.9170 -9.5581 9.6427
hospbin*age_group   3 2   9 1 0.9921 3.1070 30 0.32 0.7517 Tukey-Kramer 1.0000 0.05 -5.3532 7.3375 -9.3775 11.3618
hospbin*age_group   3 2   9 2 2.4465 4.3940 30 0.56 0.5818 Tukey-Kramer 0.9997 0.05 -6.5272 11.4202 -12.2183 17.1114
hospbin*age_group   3 2   9 3 -0.4183 2.8363 30 -0.15 0.8837 Tukey-Kramer 1.0000 0.05 -6.2108 5.3741 -9.8845 9.0478
hospbin*age_group   3 3   6 1 -0.8769 2.1970 30 -0.40 0.6926 Tukey-Kramer 1.0000 0.05 -5.3637 3.6099 -8.2093 6.4555
hospbin*age_group   3 3   6 2 1.8937 2.8363 30 0.67 0.5095 Tukey-Kramer 0.9989 0.05 -3.8988 7.6861 -7.5725 11.3598
hospbin*age_group   3 3   6 3 -2.2494 1.8568 30 -1.21 0.2352 Tukey-Kramer 0.9476 0.05 -6.0415 1.5427 -8.4464 3.9476
hospbin*age_group   3 3   9 1 -1.2996 2.1970 30 -0.59 0.5586 Tukey-Kramer 0.9995 0.05 -5.7864 3.1873 -8.6320 6.0329
hospbin*age_group   3 3   9 2 0.1548 3.8053 30 0.04 0.9678 Tukey-Kramer 1.0000 0.05 -7.6166 7.9262 -12.5453 12.8549
hospbin*age_group   3 3   9 3 -2.7100 1.7938 30 -1.51 0.1413 Tukey-Kramer 0.8418 0.05 -6.3735 0.9534 -8.6969 3.2769
hospbin*age_group   6 1   6 2 2.7706 3.1070 30 0.89 0.3796 Tukey-Kramer 0.9918 0.05 -3.5748 9.1159 -7.5991 13.1402
hospbin*age_group   6 1   6 3 -1.3725 2.2487 30 -0.61 0.5462 Tukey-Kramer 0.9994 0.05 -5.9649 3.2199 -8.8775 6.1325
hospbin*age_group   6 1   9 1 -0.4227 2.5369 30 -0.17 0.8688 Tukey-Kramer 1.0000 0.05 -5.6036 4.7583 -8.8894 8.0441
hospbin*age_group   6 1   9 2 1.0317 4.0111 30 0.26 0.7988 Tukey-Kramer 1.0000 0.05 -7.1601 9.2235 -12.3554 14.4188
hospbin*age_group   6 1   9 3 -1.8331 2.1970 30 -0.83 0.4107 Tukey-Kramer 0.9947 0.05 -6.3200 2.6537 -9.1656 5.4993
hospbin*age_group   6 2   6 3 -4.1431 2.8765 30 -1.44 0.1601 Tukey-Kramer 0.8730 0.05 -10.0177 1.7316 -13.7434 5.4573
hospbin*age_group   6 2   9 1 -3.1932 3.1070 30 -1.03 0.3123 Tukey-Kramer 0.9799 0.05 -9.5385 3.1521 -13.5628 7.1764
hospbin*age_group   6 2   9 2 -1.7389 4.3940 30 -0.40 0.6951 Tukey-Kramer 1.0000 0.05 -10.7125 7.2348 -16.4037 12.9260
hospbin*age_group   6 2   9 3 -4.6037 2.8363 30 -1.62 0.1150 Tukey-Kramer 0.7850 0.05 -10.3962 1.1888 -14.0698 4.8624
hospbin*age_group   6 3   9 1 0.9498 2.2487 30 0.42 0.6757 Tukey-Kramer 1.0000 0.05 -3.6426 5.5423 -6.5551 8.4548
hospbin*age_group   6 3   9 2 2.4042 3.8354 30 0.63 0.5355 Tukey-Kramer 0.9993 0.05 -5.4287 10.2371 -10.3963 15.2047
hospbin*age_group   6 3   9 3 -0.4606 1.8568 30 -0.25 0.8058 Tukey-Kramer 1.0000 0.05 -4.2527 3.3314 -6.6577 5.7364
hospbin*age_group   9 1   9 2 1.4544 4.0111 30 0.36 0.7195 Tukey-Kramer 1.0000 0.05 -6.7374 9.6462 -11.9328 14.8415
hospbin*age_group   9 1   9 3 -1.4105 2.1970 30 -0.64 0.5257 Tukey-Kramer 0.9991 0.05 -5.8973 3.0763 -8.7429 5.9219
hospbin*age_group   9 2   9 3 -2.8648 3.8053 30 -0.75 0.4574 Tukey-Kramer 0.9974 0.05 -10.6363 4.9066 -15.5650 9.8353
sample_type2 A     B     -0.1728 0.3664 30 -0.47 0.6405 Tukey-Kramer 0.8850 0.05 -0.9210 0.5754 -1.0760 0.7303
sample_type2 A     C     -1.0818 0.4379 30 -2.47 0.0194 Tukey-Kramer 0.0494 0.05 -1.9762 -0.1875 -2.1614 -0.00230
sample_type2 B     C     -0.9090 0.3267 30 -2.78 0.0092 Tukey-Kramer 0.0244 0.05 -1.5762 -0.2418 -1.7144 -0.1036
hospbin*sample_type2 A 3   B 3   -0.2411 0.5990 30 -0.40 0.6902 Tukey-Kramer 1.0000 0.05 -1.4644 0.9822 -2.2403 1.7581
hospbin*sample_type2 A 3   C 3   -1.3750 0.7160 30 -1.92 0.0644 Tukey-Kramer 0.6059 0.05 -2.8373 0.08723 -3.7647 1.0146
hospbin*sample_type2 A 3   A 6   0.3327 1.3994 30 0.24 0.8137 Tukey-Kramer 1.0000 0.05 -2.5253 3.1908 -4.3379 5.0034
hospbin*sample_type2 A 3   B 6   -0.1952 1.4988 30 -0.13 0.8972 Tukey-Kramer 1.0000 0.05 -3.2561 2.8657 -5.1974 4.8069
hospbin*sample_type2 A 3   C 6   -0.7333 1.7398 30 -0.42 0.6764 Tukey-Kramer 1.0000 0.05 -4.2864 2.8198 -6.5398 5.0732
hospbin*sample_type2 A 3   A 9   -0.8880 1.5712 30 -0.57 0.5761 Tukey-Kramer 0.9997 0.05 -4.0968 2.3207 -6.1318 4.3557
hospbin*sample_type2 A 3   B 9   -0.6375 1.7064 30 -0.37 0.7113 Tukey-Kramer 1.0000 0.05 -4.1225 2.8474 -6.3326 5.0576
hospbin*sample_type2 A 3   C 9   -1.6925 2.0283 30 -0.83 0.4106 Tukey-Kramer 0.9947 0.05 -5.8347 2.4498 -8.4618 5.0768
hospbin*sample_type2 B 3   C 3   -1.1339 0.5342 30 -2.12 0.0421 Tukey-Kramer 0.4778 0.05 -2.2249 -0.04297 -2.9168 0.6489
hospbin*sample_type2 B 3   A 6   0.5738 1.5058 30 0.38 0.7058 Tukey-Kramer 1.0000 0.05 -2.5014 3.6490 -4.4518 5.5994
hospbin*sample_type2 B 3   B 6   0.04586 1.5985 30 0.03 0.9773 Tukey-Kramer 1.0000 0.05 -3.2187 3.3105 -5.2892 5.3809
hospbin*sample_type2 B 3   C 6   -0.4922 1.8264 30 -0.27 0.7894 Tukey-Kramer 1.0000 0.05 -4.2223 3.2378 -6.5879 5.6034
hospbin*sample_type2 B 3   A 9   -0.6469 1.6666 30 -0.39 0.7006 Tukey-Kramer 1.0000 0.05 -4.0505 2.7567 -6.2091 4.9153
hospbin*sample_type2 B 3   B 9   -0.3964 1.7947 30 -0.22 0.8267 Tukey-Kramer 1.0000 0.05 -4.0616 3.2688 -6.3861 5.5932
hospbin*sample_type2 B 3   C 9   -1.4514 2.1030 30 -0.69 0.4954 Tukey-Kramer 0.9986 0.05 -5.7464 2.8436 -8.4703 5.5675
hospbin*sample_type2 C 3   A 6   1.7078 1.7622 30 0.97 0.3402 Tukey-Kramer 0.9860 0.05 -1.8910 5.3065 -4.1734 7.5889
hospbin*sample_type2 C 3   B 6   1.1798 1.8420 30 0.64 0.5267 Tukey-Kramer 0.9992 0.05 -2.5821 4.9417 -4.9679 7.3275
hospbin*sample_type2 C 3   C 6   0.6417 2.0429 30 0.31 0.7556 Tukey-Kramer 1.0000 0.05 -3.5305 4.8139 -6.1766 7.4600
hospbin*sample_type2 C 3   A 9   0.4870 1.9014 30 0.26 0.7996 Tukey-Kramer 1.0000 0.05 -3.3961 4.3702 -5.8589 6.8329
hospbin*sample_type2 C 3   B 9   0.7375 2.0146 30 0.37 0.7169 Tukey-Kramer 1.0000 0.05 -3.3768 4.8519 -5.9861 7.4612
hospbin*sample_type2 C 3   C 9   -0.3174 2.2936 30 -0.14 0.8909 Tukey-Kramer 1.0000 0.05 -5.0016 4.3667 -7.9723 7.3374
hospbin*sample_type2 A 6   B 6   -0.5279 0.5782 30 -0.91 0.3685 Tukey-Kramer 0.9904 0.05 -1.7088 0.6529 -2.4576 1.4017
hospbin*sample_type2 A 6   C 6   -1.0660 0.6911 30 -1.54 0.1334 Tukey-Kramer 0.8266 0.05 -2.4775 0.3454 -3.3726 1.2405
hospbin*sample_type2 A 6   A 9   -1.2207 1.5490 30 -0.79 0.4368 Tukey-Kramer 0.9964 0.05 -4.3841 1.9427 -6.3904 3.9489
hospbin*sample_type2 A 6   B 9   -0.9702 1.6860 30 -0.58 0.5693 Tukey-Kramer 0.9996 0.05 -4.4135 2.4730 -6.5972 4.6568
hospbin*sample_type2 A 6   C 9   -2.0252 2.0111 30 -1.01 0.3220 Tukey-Kramer 0.9822 0.05 -6.1324 2.0821 -8.7373 4.6869
hospbin*sample_type2 B 6   C 6   -0.5381 0.5156 30 -1.04 0.3050 Tukey-Kramer 0.9779 0.05 -1.5912 0.5149 -2.2590 1.1828
hospbin*sample_type2 B 6   A 9   -0.6928 1.6392 30 -0.42 0.6756 Tukey-Kramer 1.0000 0.05 -4.0406 2.6550 -6.1638 4.7782
hospbin*sample_type2 B 6   B 9   -0.4423 1.7693 30 -0.25 0.8043 Tukey-Kramer 1.0000 0.05 -4.0557 3.1711 -6.3473 5.4627
hospbin*sample_type2 B 6   C 9   -1.4972 2.0814 30 -0.72 0.4775 Tukey-Kramer 0.9981 0.05 -5.7481 2.7536 -8.4441 5.4496
hospbin*sample_type2 C 6   A 9   -0.1547 1.8622 30 -0.08 0.9343 Tukey-Kramer 1.0000 0.05 -3.9577 3.6483 -6.3697 6.0603
hospbin*sample_type2 C 6   B 9   0.09582 1.9776 30 0.05 0.9617 Tukey-Kramer 1.0000 0.05 -3.9430 4.1346 -6.5044 6.6961
hospbin*sample_type2 C 6   C 9   -0.9591 2.2612 30 -0.42 0.6745 Tukey-Kramer 1.0000 0.05 -5.5771 3.6588 -8.5058 6.5876
hospbin*sample_type2 A 9   B 9   0.2505 0.7175 30 0.35 0.7294 Tukey-Kramer 1.0000 0.05 -1.2148 1.7159 -2.1442 2.6452
hospbin*sample_type2 A 9   C 9   -0.8044 0.8576 30 -0.94 0.3558 Tukey-Kramer 0.9886 0.05 -2.5560 0.9471 -3.6668 2.0579
hospbin*sample_type2 B 9   C 9   -1.0550 0.6399 30 -1.65 0.1096 Tukey-Kramer 0.7710 0.05 -2.3618 0.2518 -3.1905 1.0806
age_group*sample_typ A   1 B   1 0.1229 0.5586 30 0.22 0.8273 Tukey-Kramer 1.0000 0.05 -1.0178 1.2637 -1.7413 1.9872
age_group*sample_typ A   1 C   1 -0.05874 0.6677 30 -0.09 0.9305 Tukey-Kramer 1.0000 0.05 -1.4223 1.3048 -2.2871 2.1696
age_group*sample_typ A   1 A   2 1.0182 1.7313 30 0.59 0.5609 Tukey-Kramer 0.9995 0.05 -2.5176 4.5541 -4.7601 6.7966
age_group*sample_typ A   1 B   2 1.2084 1.9085 30 0.63 0.5314 Tukey-Kramer 0.9992 0.05 -2.6892 5.1061 -5.1611 7.5780
age_group*sample_typ A   1 C   2 -0.2680 2.3218 30 -0.12 0.9089 Tukey-Kramer 1.0000 0.05 -5.0097 4.4737 -8.0170 7.4809
age_group*sample_typ A   1 A   3 -0.00846 1.1390 30 -0.01 0.9941 Tukey-Kramer 1.0000 0.05 -2.3345 2.3176 -3.8098 3.7928
age_group*sample_typ A   1 B   3 -0.8401 1.1933 30 -0.70 0.4868 Tukey-Kramer 0.9984 0.05 -3.2771 1.5969 -4.8227 3.1424
age_group*sample_typ A   1 C   3 -1.9090 1.3294 30 -1.44 0.1614 Tukey-Kramer 0.8748 0.05 -4.6240 0.8060 -6.3459 2.5279
age_group*sample_typ B   1 C   1 -0.1817 0.4981 30 -0.36 0.7179 Tukey-Kramer 1.0000 0.05 -1.1990 0.8357 -1.8442 1.4809
age_group*sample_typ B   1 A   2 0.8953 1.8073 30 0.50 0.6239 Tukey-Kramer 0.9999 0.05 -2.7956 4.5862 -5.1364 6.9270
age_group*sample_typ B   1 B   2 1.0855 1.9776 30 0.55 0.5871 Tukey-Kramer 0.9997 0.05 -2.9533 5.1243 -5.5148 7.6858
age_group*sample_typ B   1 C   2 -0.3910 2.3789 30 -0.16 0.8706 Tukey-Kramer 1.0000 0.05 -5.2494 4.4675 -8.3307 7.5487
age_group*sample_typ B   1 A   3 -0.1314 1.2514 30 -0.11 0.9171 Tukey-Kramer 1.0000 0.05 -2.6870 2.4242 -4.3078 4.0450
age_group*sample_typ B   1 B   3 -0.9631 1.3010 30 -0.74 0.4649 Tukey-Kramer 0.9977 0.05 -3.6200 1.6939 -5.3051 3.3790
age_group*sample_typ B   1 C   3 -2.0319 1.4269 30 -1.42 0.1648 Tukey-Kramer 0.8796 0.05 -4.9460 0.8822 -6.7941 2.7303
age_group*sample_typ C   1 A   2 1.0770 1.9987 30 0.54 0.5940 Tukey-Kramer 0.9998 0.05 -3.0048 5.1588 -5.5936 7.7475
age_group*sample_typ C   1 B   2 1.2672 2.1539 30 0.59 0.5607 Tukey-Kramer 0.9995 0.05 -3.1317 5.6661 -5.9216 8.4559
age_group*sample_typ C   1 C   2 -0.2093 2.5274 30 -0.08 0.9346 Tukey-Kramer 1.0000 0.05 -5.3709 4.9524 -8.6445 8.2260
age_group*sample_typ C   1 A   3 0.05029 1.5147 30 0.03 0.9737 Tukey-Kramer 1.0000 0.05 -3.0432 3.1438 -5.0051 5.1057
age_group*sample_typ C   1 B   3 -0.7814 1.5560 30 -0.50 0.6192 Tukey-Kramer 0.9999 0.05 -3.9591 2.3963 -5.9744 4.4117
age_group*sample_typ C   1 C   3 -1.8502 1.6627 30 -1.11 0.2746 Tukey-Kramer 0.9676 0.05 -5.2459 1.5454 -7.3994 3.6989
age_group*sample_typ A   2 B   2 0.1902 0.8653 30 0.22 0.8275 Tukey-Kramer 1.0000 0.05 -1.5771 1.9575 -2.6979 3.0783
age_group*sample_typ A   2 C   2 -1.2863 1.0344 30 -1.24 0.2233 Tukey-Kramer 0.9396 0.05 -3.3987 0.8262 -4.7384 2.1659
age_group*sample_typ A   2 A   3 -1.0267 1.5911 30 -0.65 0.5236 Tukey-Kramer 0.9991 0.05 -4.2761 2.2227 -6.3369 4.2835
age_group*sample_typ A   2 B   3 -1.8584 1.6304 30 -1.14 0.2634 Tukey-Kramer 0.9628 0.05 -5.1880 1.4713 -7.2998 3.5831
age_group*sample_typ A   2 C   3 -2.9272 1.7325 30 -1.69 0.1015 Tukey-Kramer 0.7479 0.05 -6.4655 0.6110 -8.7095 2.8550
age_group*sample_typ B   2 C   2 -1.4765 0.7717 30 -1.91 0.0653 Tukey-Kramer 0.6105 0.05 -3.0525 0.09961 -4.0521 1.0992
age_group*sample_typ B   2 A   3 -1.2169 1.7822 30 -0.68 0.5000 Tukey-Kramer 0.9987 0.05 -4.8567 2.4229 -7.1650 4.7313
age_group*sample_typ B   2 B   3 -2.0485 1.8174 30 -1.13 0.2686 Tukey-Kramer 0.9651 0.05 -5.7602 1.6631 -8.1141 4.0170
age_group*sample_typ B   2 C   3 -3.1174 1.9095 30 -1.63 0.1130 Tukey-Kramer 0.7799 0.05 -7.0172 0.7824 -9.4905 3.2557
age_group*sample_typ C   2 A   3 0.2596 2.2192 30 0.12 0.9077 Tukey-Kramer 1.0000 0.05 -4.2726 4.7917 -7.1469 7.6660
age_group*sample_typ C   2 B   3 -0.5721 2.2475 30 -0.25 0.8008 Tukey-Kramer 1.0000 0.05 -5.1621 4.0179 -8.0732 6.9290
age_group*sample_typ C   2 C   3 -1.6410 2.3227 30 -0.71 0.4853 Tukey-Kramer 0.9983 0.05 -6.3845 3.1026 -9.3928 6.1109
age_group*sample_typ A   3 B   3 -0.8317 0.3835 30 -2.17 0.0382 Tukey-Kramer 0.4498 0.05 -1.6149 -0.04840 -2.1117 0.4484
age_group*sample_typ A   3 C   3 -1.9005 0.4584 30 -4.15 0.0003 Tukey-Kramer 0.0068 0.05 -2.8368 -0.9643 -3.4305 -0.3705
age_group*sample_typ B   3 C   3 -1.0689 0.3420 30 -3.13 0.0039 Tukey-Kramer 0.0804 0.05 -1.7674 -0.3703 -2.2104 0.07266
hospbi*age_gr*sample A 3 1 B 3 1 -0.05697 1.0598 30 -0.05 0.9575 Tukey-Kramer 1.0000 0.05 -2.2214 2.1075 -4.3598 4.2459
hospbi*age_gr*sample A 3 1 C 3 1 -0.7139 1.2668 30 -0.56 0.5773 Tukey-Kramer 1.0000 0.05 -3.3011 1.8733 -5.8571 4.4294
hospbi*age_gr*sample A 3 1 A 3 2 -1.5871 2.8168 30 -0.56 0.5773 Tukey-Kramer 1.0000 0.05 -7.3398 4.1657 -13.0233 9.8491
hospbi*age_gr*sample A 3 1 B 3 2 -2.0319 3.0635 30 -0.66 0.5122 Tukey-Kramer 1.0000 0.05 -8.2885 4.2247 -14.4698 10.4059
hospbi*age_gr*sample A 3 1 C 3 2 -4.1433 3.6495 30 -1.14 0.2652 Tukey-Kramer 1.0000 0.05 -11.5966 3.3101 -18.9602 10.6737
hospbi*age_gr*sample A 3 1 A 3 3 0.06311 2.0890 30 0.03 0.9761 Tukey-Kramer 1.0000 0.05 -4.2032 4.3295 -8.4182 8.5444
hospbi*age_gr*sample A 3 1 B 3 3 -0.1583 2.1741 30 -0.07 0.9424 Tukey-Kramer 1.0000 0.05 -4.5984 4.2818 -8.9850 8.6684
hospbi*age_gr*sample A 3 1 C 3 3 -0.7919 2.3896 30 -0.33 0.7426 Tukey-Kramer 1.0000 0.05 -5.6721 4.0883 -10.4936 8.9097
hospbi*age_gr*sample A 3 1 A 6 1 -0.8929 2.3567 30 -0.38 0.7075 Tukey-Kramer 1.0000 0.05 -5.7060 3.9202 -10.4611 8.6753
hospbi*age_gr*sample A 3 1 B 6 1 -1.5297 2.5059 30 -0.61 0.5462 Tukey-Kramer 1.0000 0.05 -6.6474 3.5881 -11.7035 8.6442
hospbi*age_gr*sample A 3 1 C 6 1 -1.0953 2.8717 30 -0.38 0.7056 Tukey-Kramer 1.0000 0.05 -6.9600 4.7694 -12.7541 10.5636
hospbi*age_gr*sample A 3 1 A 6 2 1.3839 2.8168 30 0.49 0.6268 Tukey-Kramer 1.0000 0.05 -4.3689 7.1366 -10.0523 12.8201
hospbi*age_gr*sample A 3 1 B 6 2 1.7825 3.0635 30 0.58 0.5650 Tukey-Kramer 1.0000 0.05 -4.4741 8.0391 -10.6554 14.2203
hospbi*age_gr*sample A 3 1 C 6 2 1.6274 3.6495 30 0.45 0.6589 Tukey-Kramer 1.0000 0.05 -5.8259 9.0808 -13.1895 16.4444
hospbi*age_gr*sample A 3 1 A 6 3 -1.0168 2.1293 30 -0.48 0.6364 Tukey-Kramer 1.0000 0.05 -5.3655 3.3318 -9.6618 7.6281
hospbi*age_gr*sample A 3 1 B 6 3 -2.3624 2.2245 30 -1.06 0.2967 Tukey-Kramer 1.0000 0.05 -6.9055 2.1807 -11.3939 6.6690
hospbi*age_gr*sample A 3 1 C 6 3 -4.2561 2.4642 30 -1.73 0.0944 Tukey-Kramer 0.9875 0.05 -9.2887 0.7766 -14.2608 5.7486
hospbi*age_gr*sample A 3 1 A 9 1 -2.1962 2.3567 30 -0.93 0.3588 Tukey-Kramer 1.0000 0.05 -7.0093 2.6169 -11.7644 7.3721
hospbi*age_gr*sample A 3 1 B 9 1 -1.1336 2.5059 30 -0.45 0.6543 Tukey-Kramer 1.0000 0.05 -6.2513 3.9842 -11.3074 9.0403
hospbi*age_gr*sample A 3 1 C 9 1 -1.4561 2.8717 30 -0.51 0.6158 Tukey-Kramer 1.0000 0.05 -7.3208 4.4086 -13.1149 10.2027
hospbi*age_gr*sample A 3 1 A 9 2 0.1688 3.5631 30 0.05 0.9625 Tukey-Kramer 1.0000 0.05 -7.1079 7.4456 -14.2970 14.6346
hospbi*age_gr*sample A 3 1 B 9 2 0.7857 3.9493 30 0.20 0.8436 Tukey-Kramer 1.0000 0.05 -7.2798 8.8512 -15.2482 16.8196
hospbi*age_gr*sample A 3 1 C 9 2 -1.3773 4.8440 30 -0.28 0.7781 Tukey-Kramer 1.0000 0.05 -11.2701 8.5155 -21.0438 18.2892
hospbi*age_gr*sample A 3 1 A 9 3 -2.1607 2.0890 30 -1.03 0.3093 Tukey-Kramer 1.0000 0.05 -6.4271 2.1057 -10.6420 6.3206
hospbi*age_gr*sample A 3 1 B 9 3 -3.0886 2.1741 30 -1.42 0.1657 Tukey-Kramer 0.9990 0.05 -7.5287 1.3515 -11.9154 5.7381
hospbi*age_gr*sample A 3 1 C 9 3 -3.7680 2.3896 30 -1.58 0.1253 Tukey-Kramer 0.9959 0.05 -8.6482 1.1122 -13.4696 5.9337
hospbi*age_gr*sample B 3 1 C 3 1 -0.6569 0.9452 30 -0.70 0.4924 Tukey-Kramer 1.0000 0.05 -2.5872 1.2734 -4.4942 3.1804
hospbi*age_gr*sample B 3 1 A 3 2 -1.5301 2.9836 30 -0.51 0.6118 Tukey-Kramer 1.0000 0.05 -7.6234 4.5632 -13.6433 10.5831
hospbi*age_gr*sample B 3 1 B 3 2 -1.9750 3.2175 30 -0.61 0.5440 Tukey-Kramer 1.0000 0.05 -8.5460 4.5961 -15.0380 11.0880
hospbi*age_gr*sample B 3 1 C 3 2 -4.0863 3.7797 30 -1.08 0.2883 Tukey-Kramer 1.0000 0.05 -11.8055 3.6329 -19.4318 11.2592
hospbi*age_gr*sample B 3 1 A 3 3 0.1201 2.3089 30 0.05 0.9589 Tukey-Kramer 1.0000 0.05 -4.5954 4.8356 -9.2541 9.4942
hospbi*age_gr*sample B 3 1 B 3 3 -0.1014 2.3862 30 -0.04 0.9664 Tukey-Kramer 1.0000 0.05 -4.9746 4.7719 -9.7891 9.5864
hospbi*age_gr*sample B 3 1 C 3 3 -0.7350 2.5841 30 -0.28 0.7780 Tukey-Kramer 1.0000 0.05 -6.0123 4.5424 -11.2261 9.7562
hospbi*age_gr*sample B 3 1 A 6 1 -0.8359 2.5537 30 -0.33 0.7457 Tukey-Kramer 1.0000 0.05 -6.0513 4.3794 -11.2038 9.5320
hospbi*age_gr*sample B 3 1 B 6 1 -1.4727 2.6920 30 -0.55 0.5884 Tukey-Kramer 1.0000 0.05 -6.9705 4.0250 -12.4020 9.4566
hospbi*age_gr*sample B 3 1 C 6 1 -1.0383 3.0354 30 -0.34 0.7347 Tukey-Kramer 1.0000 0.05 -7.2374 5.1608 -13.3619 11.2853
hospbi*age_gr*sample B 3 1 A 6 2 1.4409 2.9836 30 0.48 0.6326 Tukey-Kramer 1.0000 0.05 -4.6524 7.5341 -10.6723 13.5540
hospbi*age_gr*sample B 3 1 B 6 2 1.8395 3.2175 30 0.57 0.5718 Tukey-Kramer 1.0000 0.05 -4.7316 8.4105 -11.2235 14.9025
hospbi*age_gr*sample B 3 1 C 6 2 1.6844 3.7797 30 0.45 0.6591 Tukey-Kramer 1.0000 0.05 -6.0348 9.4036 -13.6611 17.0299
hospbi*age_gr*sample B 3 1 A 6 3 -0.9599 2.3455 30 -0.41 0.6853 Tukey-Kramer 1.0000 0.05 -5.7499 3.8302 -10.4823 8.5626
hospbi*age_gr*sample B 3 1 B 6 3 -2.3055 2.4322 30 -0.95 0.3508 Tukey-Kramer 1.0000 0.05 -7.2727 2.6618 -12.1802 7.5692
hospbi*age_gr*sample B 3 1 C 6 3 -4.1991 2.6532 30 -1.58 0.1240 Tukey-Kramer 0.9957 0.05 -9.6177 1.2195 -14.9711 6.5729
hospbi*age_gr*sample B 3 1 A 9 1 -2.1392 2.5537 30 -0.84 0.4088 Tukey-Kramer 1.0000 0.05 -7.3545 3.0761 -12.5071 8.2287
hospbi*age_gr*sample B 3 1 B 9 1 -1.0766 2.6920 30 -0.40 0.6920 Tukey-Kramer 1.0000 0.05 -6.5743 4.4212 -12.0059 9.8527
hospbi*age_gr*sample B 3 1 C 9 1 -1.3991 3.0354 30 -0.46 0.6482 Tukey-Kramer 1.0000 0.05 -7.5983 4.8000 -13.7227 10.9244
hospbi*age_gr*sample B 3 1 A 9 2 0.2258 3.6963 30 0.06 0.9517 Tukey-Kramer 1.0000 0.05 -7.3230 7.7746 -14.7809 15.2325
hospbi*age_gr*sample B 3 1 B 9 2 0.8427 4.0699 30 0.21 0.8374 Tukey-Kramer 1.0000 0.05 -7.4691 9.1545 -15.6809 17.3662
hospbi*age_gr*sample B 3 1 C 9 2 -1.3203 4.9428 30 -0.27 0.7912 Tukey-Kramer 1.0000 0.05 -11.4150 8.7743 -21.3880 18.7474
hospbi*age_gr*sample B 3 1 A 9 3 -2.1037 2.3089 30 -0.91 0.3695 Tukey-Kramer 1.0000 0.05 -6.8192 2.6117 -11.4779 7.2704
hospbi*age_gr*sample B 3 1 B 9 3 -3.0317 2.3862 30 -1.27 0.2137 Tukey-Kramer 0.9998 0.05 -7.9049 1.8416 -12.7194 6.6561
hospbi*age_gr*sample B 3 1 C 9 3 -3.7110 2.5841 30 -1.44 0.1613 Tukey-Kramer 0.9989 0.05 -8.9883 1.5663 -14.2021 6.7801
hospbi*age_gr*sample C 3 1 A 3 2 -0.8732 3.3947 30 -0.26 0.7988 Tukey-Kramer 1.0000 0.05 -7.8062 6.0598 -14.6557 12.9093
hospbi*age_gr*sample C 3 1 B 3 2 -1.3181 3.6021 30 -0.37 0.7170 Tukey-Kramer 1.0000 0.05 -8.6745 6.0384 -15.9424 13.3062
hospbi*age_gr*sample C 3 1 C 3 2 -3.4294 4.1120 30 -0.83 0.4109 Tukey-Kramer 1.0000 0.05 -11.8273 4.9685 -20.1241 13.2653
hospbi*age_gr*sample C 3 1 A 3 3 0.7770 2.8202 30 0.28 0.7848 Tukey-Kramer 1.0000 0.05 -4.9827 6.5367 -10.6730 12.2270
hospbi*age_gr*sample C 3 1 B 3 3 0.5556 2.8838 30 0.19 0.8485 Tukey-Kramer 1.0000 0.05 -5.3340 6.4451 -11.1526 12.2637
hospbi*age_gr*sample C 3 1 C 3 3 -0.07806 3.0496 30 -0.03 0.9797 Tukey-Kramer 1.0000 0.05 -6.3061 6.1500 -12.4592 12.3031
hospbi*age_gr*sample C 3 1 A 6 1 -0.1790 3.0239 30 -0.06 0.9532 Tukey-Kramer 1.0000 0.05 -6.3546 5.9966 -12.4559 12.0979
hospbi*age_gr*sample C 3 1 B 6 1 -0.8158 3.1415 30 -0.26 0.7969 Tukey-Kramer 1.0000 0.05 -7.2317 5.6001 -13.5703 11.9387
hospbi*age_gr*sample C 3 1 C 6 1 -0.3814 3.4404 30 -0.11 0.9125 Tukey-Kramer 1.0000 0.05 -7.4076 6.6448 -14.3492 13.5864
hospbi*age_gr*sample C 3 1 A 6 2 2.0978 3.3947 30 0.62 0.5413 Tukey-Kramer 1.0000 0.05 -4.8352 9.0308 -11.6847 15.8803
hospbi*age_gr*sample C 3 1 B 6 2 2.4964 3.6021 30 0.69 0.4936 Tukey-Kramer 1.0000 0.05 -4.8601 9.8528 -12.1279 17.1207
hospbi*age_gr*sample C 3 1 C 6 2 2.3413 4.1120 30 0.57 0.5733 Tukey-Kramer 1.0000 0.05 -6.0566 10.7392 -14.3534 19.0360
hospbi*age_gr*sample C 3 1 A 6 3 -0.3029 2.8502 30 -0.11 0.9161 Tukey-Kramer 1.0000 0.05 -6.1239 5.5180 -11.8747 11.2688
hospbi*age_gr*sample C 3 1 B 6 3 -1.6486 2.9220 30 -0.56 0.5768 Tukey-Kramer 1.0000 0.05 -7.6162 4.3190 -13.5119 10.2147
hospbi*age_gr*sample C 3 1 C 6 3 -3.5422 3.1084 30 -1.14 0.2635 Tukey-Kramer 1.0000 0.05 -9.8904 2.8060 -16.1622 9.0778
hospbi*age_gr*sample C 3 1 A 9 1 -1.4823 3.0239 30 -0.49 0.6276 Tukey-Kramer 1.0000 0.05 -7.6579 4.6933 -13.7591 10.7946
hospbi*age_gr*sample C 3 1 B 9 1 -0.4197 3.1415 30 -0.13 0.8946 Tukey-Kramer 1.0000 0.05 -6.8356 5.9962 -13.1742 12.3348
hospbi*age_gr*sample C 3 1 C 9 1 -0.7422 3.4404 30 -0.22 0.8307 Tukey-Kramer 1.0000 0.05 -7.7684 6.2840 -14.7100 13.2256
hospbi*age_gr*sample C 3 1 A 9 2 0.8827 4.0355 30 0.22 0.8283 Tukey-Kramer 1.0000 0.05 -7.3588 9.1243 -15.5011 17.2665
hospbi*age_gr*sample C 3 1 B 9 2 1.4996 4.3802 30 0.34 0.7345 Tukey-Kramer 1.0000 0.05 -7.4461 10.4452 -16.2840 19.2832
hospbi*age_gr*sample C 3 1 C 9 2 -0.6634 5.2014 30 -0.13 0.8994 Tukey-Kramer 1.0000 0.05 -11.2860 9.9592 -21.7807 20.4539
hospbi*age_gr*sample C 3 1 A 9 3 -1.4468 2.8202 30 -0.51 0.6117 Tukey-Kramer 1.0000 0.05 -7.2065 4.3129 -12.8968 10.0032
hospbi*age_gr*sample C 3 1 B 9 3 -2.3747 2.8838 30 -0.82 0.4167 Tukey-Kramer 1.0000 0.05 -8.2643 3.5148 -14.0829 9.3334
hospbi*age_gr*sample C 3 1 C 9 3 -3.0541 3.0496 30 -1.00 0.3246 Tukey-Kramer 1.0000 0.05 -9.2821 3.1740 -15.4352 9.3270
hospbi*age_gr*sample A 3 2 B 3 2 -0.4449 1.2980 30 -0.34 0.7342 Tukey-Kramer 1.0000 0.05 -3.0958 2.2060 -5.7148 4.8250
hospbi*age_gr*sample A 3 2 C 3 2 -2.5562 1.5515 30 -1.65 0.1099 Tukey-Kramer 0.9929 0.05 -5.7248 0.6125 -8.8553 3.7430
hospbi*age_gr*sample A 3 2 A 3 3 1.6502 2.4395 30 0.68 0.5039 Tukey-Kramer 1.0000 0.05 -3.3318 6.6322 -8.2539 11.5542
hospbi*age_gr*sample A 3 2 B 3 3 1.4287 2.5127 30 0.57 0.5739 Tukey-Kramer 1.0000 0.05 -3.7029 6.5604 -8.7727 11.6301
hospbi*age_gr*sample A 3 2 C 3 3 0.7951 2.7013 30 0.29 0.7705 Tukey-Kramer 1.0000 0.05 -4.7217 6.3119 -10.1721 11.7623
hospbi*age_gr*sample A 3 2 A 6 1 0.6942 2.6723 30 0.26 0.7968 Tukey-Kramer 1.0000 0.05 -4.7634 6.1517 -10.1552 11.5435
hospbi*age_gr*sample A 3 2 B 6 1 0.05739 2.8047 30 0.02 0.9838 Tukey-Kramer 1.0000 0.05 -5.6706 5.7854 -11.3297 11.4444
hospbi*age_gr*sample A 3 2 C 6 1 0.4918 3.1358 30 0.16 0.8764 Tukey-Kramer 1.0000 0.05 -5.9124 6.8960 -12.2395 13.2231
hospbi*age_gr*sample A 3 2 A 6 2 2.9710 3.0857 30 0.96 0.3433 Tukey-Kramer 1.0000 0.05 -3.3309 9.2728 -9.5568 15.4987
hospbi*age_gr*sample A 3 2 B 6 2 3.3696 3.3124 30 1.02 0.3172 Tukey-Kramer 1.0000 0.05 -3.3953 10.1345 -10.0788 16.8179
hospbi*age_gr*sample A 3 2 C 6 2 3.2145 3.8608 30 0.83 0.4117 Tukey-Kramer 1.0000 0.05 -4.6704 11.0994 -12.4603 18.8893
hospbi*age_gr*sample A 3 2 A 6 3 0.5702 2.4741 30 0.23 0.8193 Tukey-Kramer 1.0000 0.05 -4.4825 5.6229 -9.4743 10.6148
hospbi*age_gr*sample A 3 2 B 6 3 -0.7754 2.5565 30 -0.30 0.7638 Tukey-Kramer 1.0000 0.05 -5.9964 4.4456 -11.1544 9.6037
hospbi*age_gr*sample A 3 2 C 6 3 -2.6690 2.7676 30 -0.96 0.3426 Tukey-Kramer 1.0000 0.05 -8.3211 2.9831 -13.9052 8.5672
hospbi*age_gr*sample A 3 2 A 9 1 -0.6091 2.6723 30 -0.23 0.8212 Tukey-Kramer 1.0000 0.05 -6.0666 4.8484 -11.4584 10.2403
hospbi*age_gr*sample A 3 2 B 9 1 0.4535 2.8047 30 0.16 0.8726 Tukey-Kramer 1.0000 0.05 -5.2745 6.1815 -10.9335 11.8406
hospbi*age_gr*sample A 3 2 C 9 1 0.1310 3.1358 30 0.04 0.9670 Tukey-Kramer 1.0000 0.05 -6.2732 6.5352 -12.6003 12.8623
hospbi*age_gr*sample A 3 2 A 9 2 1.7559 3.7792 30 0.46 0.6456 Tukey-Kramer 1.0000 0.05 -5.9622 9.4740 -13.5874 17.0992
hospbi*age_gr*sample A 3 2 B 9 2 2.3728 4.1453 30 0.57 0.5713 Tukey-Kramer 1.0000 0.05 -6.0931 10.8387 -14.4570 19.2026
hospbi*age_gr*sample A 3 2 C 9 2 0.2098 5.0051 30 0.04 0.9668 Tukey-Kramer 1.0000 0.05 -10.0121 10.4316 -20.1108 20.5304
hospbi*age_gr*sample A 3 2 A 9 3 -0.5736 2.4395 30 -0.24 0.8157 Tukey-Kramer 1.0000 0.05 -5.5557 4.4084 -10.4777 9.3304
hospbi*age_gr*sample A 3 2 B 9 3 -1.5016 2.5127 30 -0.60 0.5546 Tukey-Kramer 1.0000 0.05 -6.6332 3.6300 -11.7030 8.6998
hospbi*age_gr*sample A 3 2 C 9 3 -2.1809 2.7013 30 -0.81 0.4258 Tukey-Kramer 1.0000 0.05 -7.6977 3.3359 -13.1481 8.7863
hospbi*age_gr*sample B 3 2 C 3 2 -2.1113 1.1576 30 -1.82 0.0781 Tukey-Kramer 0.9771 0.05 -4.4754 0.2528 -6.8110 2.5884
hospbi*age_gr*sample B 3 2 A 3 3 2.0951 2.7206 30 0.77 0.4473 Tukey-Kramer 1.0000 0.05 -3.4612 7.6513 -8.9504 13.1406
hospbi*age_gr*sample B 3 2 B 3 3 1.8736 2.7865 30 0.67 0.5065 Tukey-Kramer 1.0000 0.05 -3.8171 7.5643 -9.4393 13.1865
hospbi*age_gr*sample B 3 2 C 3 3 1.2400 2.9577 30 0.42 0.6780 Tukey-Kramer 1.0000 0.05 -4.8004 7.2804 -10.7680 13.2480
hospbi*age_gr*sample B 3 2 A 6 1 1.1391 2.9312 30 0.39 0.7003 Tukey-Kramer 1.0000 0.05 -4.8472 7.1253 -10.7614 13.0395
hospbi*age_gr*sample B 3 2 B 6 1 0.5023 3.0524 30 0.16 0.8704 Tukey-Kramer 1.0000 0.05 -5.7316 6.7361 -11.8904 12.8949
hospbi*age_gr*sample B 3 2 C 6 1 0.9366 3.3592 30 0.28 0.7823 Tukey-Kramer 1.0000 0.05 -5.9237 7.7970 -12.7015 14.5748
hospbi*age_gr*sample B 3 2 A 6 2 3.4158 3.3124 30 1.03 0.3107 Tukey-Kramer 1.0000 0.05 -3.3491 10.1807 -10.0325 16.8642
hospbi*age_gr*sample B 3 2 B 6 2 3.8144 3.5246 30 1.08 0.2878 Tukey-Kramer 1.0000 0.05 -3.3838 11.0127 -10.4954 18.1242
hospbi*age_gr*sample B 3 2 C 6 2 3.6594 4.0444 30 0.90 0.3728 Tukey-Kramer 1.0000 0.05 -4.6003 11.9191 -12.7605 20.0793
hospbi*age_gr*sample B 3 2 A 6 3 1.0151 2.7517 30 0.37 0.7148 Tukey-Kramer 1.0000 0.05 -4.6045 6.6348 -10.1565 12.1868
hospbi*age_gr*sample B 3 2 B 6 3 -0.3305 2.8260 30 -0.12 0.9077 Tukey-Kramer 1.0000 0.05 -6.1019 5.4409 -11.8039 11.1429
hospbi*age_gr*sample B 3 2 C 6 3 -2.2241 3.0183 30 -0.74 0.4669 Tukey-Kramer 1.0000 0.05 -8.3883 3.9401 -14.4783 10.0300
hospbi*age_gr*sample B 3 2 A 9 1 -0.1642 2.9312 30 -0.06 0.9557 Tukey-Kramer 1.0000 0.05 -6.1505 5.8221 -12.0647 11.7363
hospbi*age_gr*sample B 3 2 B 9 1 0.8984 3.0524 30 0.29 0.7705 Tukey-Kramer 1.0000 0.05 -5.3355 7.1322 -11.4943 13.2910
hospbi*age_gr*sample B 3 2 C 9 1 0.5758 3.3592 30 0.17 0.8650 Tukey-Kramer 1.0000 0.05 -6.2845 7.4362 -13.0623 14.2140
hospbi*age_gr*sample B 3 2 A 9 2 2.2008 3.9665 30 0.55 0.5831 Tukey-Kramer 1.0000 0.05 -5.8999 10.3014 -13.9029 18.3045
hospbi*age_gr*sample B 3 2 B 9 2 2.8176 4.3168 30 0.65 0.5189 Tukey-Kramer 1.0000 0.05 -5.9984 11.6337 -14.7082 20.3435
hospbi*age_gr*sample B 3 2 C 9 2 0.6546 5.1480 30 0.13 0.8997 Tukey-Kramer 1.0000 0.05 -9.8590 11.1683 -20.2461 21.5554
hospbi*age_gr*sample B 3 2 A 9 3 -0.1288 2.7206 30 -0.05 0.9626 Tukey-Kramer 1.0000 0.05 -5.6850 5.4275 -11.1743 10.9168
hospbi*age_gr*sample B 3 2 B 9 3 -1.0567 2.7865 30 -0.38 0.7072 Tukey-Kramer 1.0000 0.05 -6.7474 4.6340 -12.3696 10.2562
hospbi*age_gr*sample B 3 2 C 9 3 -1.7360 2.9577 30 -0.59 0.5616 Tukey-Kramer 1.0000 0.05 -7.7764 4.3044 -13.7440 10.2720
hospbi*age_gr*sample C 3 2 A 3 3 4.2064 3.3668 30 1.25 0.2212 Tukey-Kramer 0.9999 0.05 -2.6696 11.0824 -9.4628 17.8755
hospbi*age_gr*sample C 3 2 B 3 3 3.9849 3.4203 30 1.17 0.2532 Tukey-Kramer 1.0000 0.05 -3.0002 10.9701 -9.9012 17.8710
hospbi*age_gr*sample C 3 2 C 3 3 3.3513 3.5611 30 0.94 0.3542 Tukey-Kramer 1.0000 0.05 -3.9215 10.6241 -11.1067 17.8093
hospbi*age_gr*sample C 3 2 A 6 1 3.2504 3.5392 30 0.92 0.3657 Tukey-Kramer 1.0000 0.05 -3.9776 10.4783 -11.1185 17.6192
hospbi*age_gr*sample C 3 2 B 6 1 2.6136 3.6402 30 0.72 0.4783 Tukey-Kramer 1.0000 0.05 -4.8207 10.0479 -12.1655 17.3926
hospbi*age_gr*sample C 3 2 C 6 1 3.0480 3.9010 30 0.78 0.4407 Tukey-Kramer 1.0000 0.05 -4.9190 11.0149 -12.7900 18.8859
hospbi*age_gr*sample C 3 2 A 6 2 5.5272 3.8608 30 1.43 0.1626 Tukey-Kramer 0.9989 0.05 -2.3577 13.4120 -10.1477 21.2020
hospbi*age_gr*sample C 3 2 B 6 2 5.9257 4.0444 30 1.47 0.1533 Tukey-Kramer 0.9985 0.05 -2.3339 14.1854 -10.4942 22.3456
hospbi*age_gr*sample C 3 2 C 6 2 5.7707 4.5045 30 1.28 0.2100 Tukey-Kramer 0.9998 0.05 -3.4288 14.9701 -12.5174 24.0588
hospbi*age_gr*sample C 3 2 A 6 3 3.1264 3.3920 30 0.92 0.3640 Tukey-Kramer 1.0000 0.05 -3.8009 10.0538 -10.6449 16.8977
hospbi*age_gr*sample C 3 2 B 6 3 1.7808 3.4525 30 0.52 0.6098 Tukey-Kramer 1.0000 0.05 -5.2702 8.8318 -12.2363 15.7980
hospbi*age_gr*sample C 3 2 C 6 3 -0.1128 3.6117 30 -0.03 0.9753 Tukey-Kramer 1.0000 0.05 -7.4888 7.2632 -14.7759 14.5503
hospbi*age_gr*sample C 3 2 A 9 1 1.9471 3.5392 30 0.55 0.5863 Tukey-Kramer 1.0000 0.05 -5.2809 9.1750 -12.4218 16.3159
hospbi*age_gr*sample C 3 2 B 9 1 3.0097 3.6402 30 0.83 0.4149 Tukey-Kramer 1.0000 0.05 -4.4246 10.4440 -11.7694 17.7887
hospbi*age_gr*sample C 3 2 C 9 1 2.6872 3.9010 30 0.69 0.4962 Tukey-Kramer 1.0000 0.05 -5.2798 10.6541 -13.1508 18.5251
hospbi*age_gr*sample C 3 2 A 9 2 4.3121 4.4347 30 0.97 0.3387 Tukey-Kramer 1.0000 0.05 -4.7448 13.3690 -13.6927 22.3169
hospbi*age_gr*sample C 3 2 B 9 2 4.9290 4.7506 30 1.04 0.3078 Tukey-Kramer 1.0000 0.05 -4.7731 14.6310 -14.3583 24.2162
hospbi*age_gr*sample C 3 2 C 9 2 2.7660 5.5169 30 0.50 0.6198 Tukey-Kramer 1.0000 0.05 -8.5010 14.0330 -19.6323 25.1642
hospbi*age_gr*sample C 3 2 A 9 3 1.9826 3.3668 30 0.59 0.5604 Tukey-Kramer 1.0000 0.05 -4.8934 8.8585 -11.6866 15.6517
hospbi*age_gr*sample C 3 2 B 9 3 1.0546 3.4203 30 0.31 0.7600 Tukey-Kramer 1.0000 0.05 -5.9305 8.0397 -12.8315 14.9407
hospbi*age_gr*sample C 3 2 C 9 3 0.3753 3.5611 30 0.11 0.9168 Tukey-Kramer 1.0000 0.05 -6.8975 7.6481 -14.0827 14.8333
hospbi*age_gr*sample A 3 3 B 3 3 -0.2214 0.6490 30 -0.34 0.7353 Tukey-Kramer 1.0000 0.05 -1.5469 1.1040 -2.8564 2.4135
hospbi*age_gr*sample A 3 3 C 3 3 -0.8551 0.7758 30 -1.10 0.2791 Tukey-Kramer 1.0000 0.05 -2.4394 0.7293 -4.0046 2.2945
hospbi*age_gr*sample A 3 3 A 6 1 -0.9560 1.8896 30 -0.51 0.6166 Tukey-Kramer 1.0000 0.05 -4.8151 2.9031 -8.6276 6.7157
hospbi*age_gr*sample A 3 3 B 6 1 -1.5928 2.0727 30 -0.77 0.4482 Tukey-Kramer 1.0000 0.05 -5.8257 2.6401 -10.0077 6.8221
hospbi*age_gr*sample A 3 3 C 6 1 -1.1584 2.5026 30 -0.46 0.6468 Tukey-Kramer 1.0000 0.05 -6.2693 3.9525 -11.3187 9.0019
hospbi*age_gr*sample A 3 3 A 6 2 1.3208 2.4395 30 0.54 0.5922 Tukey-Kramer 1.0000 0.05 -3.6612 6.3028 -8.5833 11.2248
hospbi*age_gr*sample A 3 3 B 6 2 1.7194 2.7206 30 0.63 0.5322 Tukey-Kramer 1.0000 0.05 -3.8368 7.2756 -9.3261 12.7649
hospbi*age_gr*sample A 3 3 C 6 2 1.5643 3.3668 30 0.46 0.6456 Tukey-Kramer 1.0000 0.05 -5.3117 8.4403 -12.1048 15.2335
hospbi*age_gr*sample A 3 3 A 6 3 -1.0799 1.5970 30 -0.68 0.5041 Tukey-Kramer 1.0000 0.05 -4.3414 2.1816 -7.5637 5.4038
hospbi*age_gr*sample A 3 3 B 6 3 -2.4256 1.7219 30 -1.41 0.1692 Tukey-Kramer 0.9991 0.05 -5.9421 1.0910 -9.4163 4.5652
hospbi*age_gr*sample A 3 3 C 6 3 -4.3192 2.0221 30 -2.14 0.0410 Tukey-Kramer 0.9004 0.05 -8.4489 -0.1895 -12.5288 3.8904
hospbi*age_gr*sample A 3 3 A 9 1 -2.2593 1.8896 30 -1.20 0.2412 Tukey-Kramer 0.9999 0.05 -6.1183 1.5998 -9.9309 5.4124
hospbi*age_gr*sample A 3 3 B 9 1 -1.1967 2.0727 30 -0.58 0.5680 Tukey-Kramer 1.0000 0.05 -5.4296 3.0363 -9.6116 7.2182
hospbi*age_gr*sample A 3 3 C 9 1 -1.5192 2.5026 30 -0.61 0.5484 Tukey-Kramer 1.0000 0.05 -6.6301 3.5917 -11.6795 8.6411
hospbi*age_gr*sample A 3 3 A 9 2 0.1057 3.2729 30 0.03 0.9744 Tukey-Kramer 1.0000 0.05 -6.5784 6.7898 -13.1820 13.3934
hospbi*age_gr*sample A 3 3 B 9 2 0.7226 3.6896 30 0.20 0.8461 Tukey-Kramer 1.0000 0.05 -6.8126 8.2578 -14.2570 15.7022
hospbi*age_gr*sample A 3 3 C 9 2 -1.4404 4.6347 30 -0.31 0.7581 Tukey-Kramer 1.0000 0.05 -10.9058 8.0250 -20.2572 17.3764
hospbi*age_gr*sample A 3 3 A 9 3 -2.2238 1.5428 30 -1.44 0.1598 Tukey-Kramer 0.9988 0.05 -5.3747 0.9271 -8.4877 4.0401
hospbi*age_gr*sample A 3 3 B 9 3 -3.1517 1.6562 30 -1.90 0.0667 Tukey-Kramer 0.9645 0.05 -6.5342 0.2307 -9.8759 3.5724
hospbi*age_gr*sample A 3 3 C 9 3 -3.8311 1.9304 30 -1.98 0.0564 Tukey-Kramer 0.9470 0.05 -7.7735 0.1114 -11.6685 4.0063
hospbi*age_gr*sample B 3 3 C 3 3 -0.6336 0.5788 30 -1.09 0.2823 Tukey-Kramer 1.0000 0.05 -1.8157 0.5484 -2.9835 1.7162
hospbi*age_gr*sample B 3 3 A 6 1 -0.7346 1.9832 30 -0.37 0.7137 Tukey-Kramer 1.0000 0.05 -4.7849 3.3158 -8.7864 7.3173
hospbi*age_gr*sample B 3 3 B 6 1 -1.3714 2.1584 30 -0.64 0.5300 Tukey-Kramer 1.0000 0.05 -5.7794 3.0366 -10.1343 7.3916
hospbi*age_gr*sample B 3 3 C 6 1 -0.9370 2.5740 30 -0.36 0.7184 Tukey-Kramer 1.0000 0.05 -6.1938 4.3199 -11.3873 9.5134
hospbi*age_gr*sample B 3 3 A 6 2 1.5422 2.5127 30 0.61 0.5440 Tukey-Kramer 1.0000 0.05 -3.5894 6.6738 -8.6592 11.7436
hospbi*age_gr*sample B 3 3 B 6 2 1.9408 2.7865 30 0.70 0.4915 Tukey-Kramer 1.0000 0.05 -3.7499 7.6315 -9.3721 13.2537
hospbi*age_gr*sample B 3 3 C 6 2 1.7857 3.4203 30 0.52 0.6054 Tukey-Kramer 1.0000 0.05 -5.1994 8.7709 -12.1004 15.6719
hospbi*age_gr*sample B 3 3 A 6 3 -0.8585 1.7068 30 -0.50 0.6186 Tukey-Kramer 1.0000 0.05 -4.3442 2.6272 -7.7879 6.0709
hospbi*age_gr*sample B 3 3 B 6 3 -2.2041 1.8242 30 -1.21 0.2364 Tukey-Kramer 0.9999 0.05 -5.9296 1.5213 -9.6101 5.2019
hospbi*age_gr*sample B 3 3 C 6 3 -4.0978 2.1099 30 -1.94 0.0616 Tukey-Kramer 0.9568 0.05 -8.4067 0.2112 -12.6637 4.4682
hospbi*age_gr*sample B 3 3 A 9 1 -2.0378 1.9832 30 -1.03 0.3124 Tukey-Kramer 1.0000 0.05 -6.0882 2.0125 -10.0897 6.0140
hospbi*age_gr*sample B 3 3 B 9 1 -0.9752 2.1584 30 -0.45 0.6546 Tukey-Kramer 1.0000 0.05 -5.3832 3.4328 -9.7382 7.7877
hospbi*age_gr*sample B 3 3 C 9 1 -1.2978 2.5740 30 -0.50 0.6178 Tukey-Kramer 1.0000 0.05 -6.5546 3.9591 -11.7481 9.1526
hospbi*age_gr*sample B 3 3 A 9 2 0.3272 3.3278 30 0.10 0.9223 Tukey-Kramer 1.0000 0.05 -6.4692 7.1235 -13.1836 13.8379
hospbi*age_gr*sample B 3 3 B 9 2 0.9440 3.7384 30 0.25 0.8024 Tukey-Kramer 1.0000 0.05 -6.6909 8.5789 -14.2338 16.1219
hospbi*age_gr*sample B 3 3 C 9 2 -1.2190 4.6737 30 -0.26 0.7960 Tukey-Kramer 1.0000 0.05 -10.7640 8.3260 -20.1940 17.7561
hospbi*age_gr*sample B 3 3 A 9 3 -2.0024 1.6562 30 -1.21 0.2361 Tukey-Kramer 0.9999 0.05 -5.3848 1.3801 -8.7265 4.7218
hospbi*age_gr*sample B 3 3 B 9 3 -2.9303 1.7623 30 -1.66 0.1068 Tukey-Kramer 0.9920 0.05 -6.5294 0.6688 -10.0852 4.2246
hospbi*age_gr*sample B 3 3 C 9 3 -3.6096 2.0222 30 -1.79 0.0844 Tukey-Kramer 0.9818 0.05 -7.7395 0.5202 -11.8196 4.6003
hospbi*age_gr*sample C 3 3 A 6 1 -0.1009 2.2174 30 -0.05 0.9640 Tukey-Kramer 1.0000 0.05 -4.6294 4.4275 -9.1033 8.9014
hospbi*age_gr*sample C 3 3 B 6 1 -0.7377 2.3753 30 -0.31 0.7583 Tukey-Kramer 1.0000 0.05 -5.5888 4.1133 -10.3814 8.9059
hospbi*age_gr*sample C 3 3 C 6 1 -0.3034 2.7584 30 -0.11 0.9132 Tukey-Kramer 1.0000 0.05 -5.9369 5.3301 -11.5025 10.8958
hospbi*age_gr*sample C 3 3 A 6 2 2.1758 2.7013 30 0.81 0.4269 Tukey-Kramer 1.0000 0.05 -3.3410 7.6927 -8.7914 13.1430
hospbi*age_gr*sample C 3 3 B 6 2 2.5744 2.9577 30 0.87 0.3910 Tukey-Kramer 1.0000 0.05 -3.4659 8.6148 -9.4336 14.5824
hospbi*age_gr*sample C 3 3 C 6 2 2.4194 3.5611 30 0.68 0.5021 Tukey-Kramer 1.0000 0.05 -4.8534 9.6922 -12.0387 16.8774
hospbi*age_gr*sample C 3 3 A 6 3 -0.2249 1.9740 30 -0.11 0.9101 Tukey-Kramer 1.0000 0.05 -4.2563 3.8065 -8.2391 7.7893
hospbi*age_gr*sample C 3 3 B 6 3 -1.5705 2.0763 30 -0.76 0.4553 Tukey-Kramer 1.0000 0.05 -5.8109 2.6699 -10.0002 6.8592
hospbi*age_gr*sample C 3 3 C 6 3 -3.4641 2.3313 30 -1.49 0.1477 Tukey-Kramer 0.9982 0.05 -8.2253 1.2970 -12.9291 6.0009
hospbi*age_gr*sample C 3 3 A 9 1 -1.4042 2.2174 30 -0.63 0.5313 Tukey-Kramer 1.0000 0.05 -5.9327 3.1242 -10.4066 7.5982
hospbi*age_gr*sample C 3 3 B 9 1 -0.3416 2.3753 30 -0.14 0.8866 Tukey-Kramer 1.0000 0.05 -5.1926 4.5094 -9.9852 9.3020
hospbi*age_gr*sample C 3 3 C 9 1 -0.6642 2.7584 30 -0.24 0.8114 Tukey-Kramer 1.0000 0.05 -6.2977 4.9693 -11.8633 10.5350
hospbi*age_gr*sample C 3 3 A 9 2 0.9608 3.4724 30 0.28 0.7839 Tukey-Kramer 1.0000 0.05 -6.1309 8.0524 -13.1371 15.0587
hospbi*age_gr*sample C 3 3 B 9 2 1.5776 3.8677 30 0.41 0.6862 Tukey-Kramer 1.0000 0.05 -6.3213 9.4766 -14.1251 17.2804
hospbi*age_gr*sample C 3 3 C 9 2 -0.5854 4.7778 30 -0.12 0.9033 Tukey-Kramer 1.0000 0.05 -10.3429 9.1721 -19.9828 18.8121
hospbi*age_gr*sample C 3 3 A 9 3 -1.3688 1.9304 30 -0.71 0.4838 Tukey-Kramer 1.0000 0.05 -5.3112 2.5737 -9.2062 6.4686
hospbi*age_gr*sample C 3 3 B 9 3 -2.2967 2.0222 30 -1.14 0.2651 Tukey-Kramer 1.0000 0.05 -6.4265 1.8332 -10.5066 5.9133
hospbi*age_gr*sample C 3 3 C 9 3 -2.9760 2.2523 30 -1.32 0.1964 Tukey-Kramer 0.9997 0.05 -7.5758 1.6237 -12.1201 6.1680
hospbi*age_gr*sample A 6 1 B 6 1 -0.6368 0.9178 30 -0.69 0.4931 Tukey-Kramer 1.0000 0.05 -2.5113 1.2377 -4.3632 3.0896
hospbi*age_gr*sample A 6 1 C 6 1 -0.2024 1.0971 30 -0.18 0.8549 Tukey-Kramer 1.0000 0.05 -2.4430 2.0382 -4.6566 4.2518
hospbi*age_gr*sample A 6 1 A 6 2 2.2768 2.6723 30 0.85 0.4010 Tukey-Kramer 1.0000 0.05 -3.1808 7.7343 -8.5726 13.1261
hospbi*age_gr*sample A 6 1 B 6 2 2.6754 2.9312 30 0.91 0.3687 Tukey-Kramer 1.0000 0.05 -3.3109 8.6617 -9.2251 14.5758
hospbi*age_gr*sample A 6 1 C 6 2 2.5203 3.5392 30 0.71 0.4819 Tukey-Kramer 1.0000 0.05 -4.7076 9.7483 -11.8485 16.8892
hospbi*age_gr*sample A 6 1 A 6 3 -0.1239 1.9341 30 -0.06 0.9493 Tukey-Kramer 1.0000 0.05 -4.0738 3.8259 -7.9761 7.7282
hospbi*age_gr*sample A 6 1 B 6 3 -1.4696 2.0384 30 -0.72 0.4765 Tukey-Kramer 1.0000 0.05 -5.6325 2.6934 -9.7454 6.8062
hospbi*age_gr*sample A 6 1 C 6 3 -3.3632 2.2976 30 -1.46 0.1537 Tukey-Kramer 0.9985 0.05 -8.0556 1.3292 -12.6914 5.9650
hospbi*age_gr*sample A 6 1 A 9 1 -1.3033 2.1819 30 -0.60 0.5548 Tukey-Kramer 1.0000 0.05 -5.7593 3.1528 -10.1617 7.5552
hospbi*age_gr*sample A 6 1 B 9 1 -0.2407 2.3422 30 -0.10 0.9188 Tukey-Kramer 1.0000 0.05 -5.0242 4.5428 -9.7501 9.2687
hospbi*age_gr*sample A 6 1 C 9 1 -0.5632 2.7300 30 -0.21 0.8379 Tukey-Kramer 1.0000 0.05 -6.1387 5.0122 -11.6470 10.5206
hospbi*age_gr*sample A 6 1 A 9 2 1.0617 3.4499 30 0.31 0.7604 Tukey-Kramer 1.0000 0.05 -5.9839 8.1074 -12.9447 15.0682
hospbi*age_gr*sample A 6 1 B 9 2 1.6786 3.8475 30 0.44 0.6658 Tukey-Kramer 1.0000 0.05 -6.1791 9.5363 -13.9421 17.2993
hospbi*age_gr*sample A 6 1 C 9 2 -0.4844 4.7614 30 -0.10 0.9196 Tukey-Kramer 1.0000 0.05 -10.2085 9.2397 -19.8155 18.8467
hospbi*age_gr*sample A 6 1 A 9 3 -1.2678 1.8896 30 -0.67 0.5074 Tukey-Kramer 1.0000 0.05 -5.1269 2.5912 -8.9395 6.4038
hospbi*age_gr*sample A 6 1 B 9 3 -2.1957 1.9832 30 -1.11 0.2770 Tukey-Kramer 1.0000 0.05 -6.2461 1.8546 -10.2476 5.8561
hospbi*age_gr*sample A 6 1 C 9 3 -2.8751 2.2174 30 -1.30 0.2046 Tukey-Kramer 0.9998 0.05 -7.4035 1.6534 -11.8775 6.1273
hospbi*age_gr*sample B 6 1 C 6 1 0.4344 0.8185 30 0.53 0.5995 Tukey-Kramer 1.0000 0.05 -1.2373 2.1061 -2.8888 3.7576
hospbi*age_gr*sample B 6 1 A 6 2 2.9136 2.8047 30 1.04 0.3072 Tukey-Kramer 1.0000 0.05 -2.8144 8.6416 -8.4735 14.3006
hospbi*age_gr*sample B 6 1 B 6 2 3.3122 3.0524 30 1.09 0.2865 Tukey-Kramer 1.0000 0.05 -2.9217 9.5460 -9.0805 15.7048
hospbi*age_gr*sample B 6 1 C 6 2 3.1571 3.6402 30 0.87 0.3927 Tukey-Kramer 1.0000 0.05 -4.2772 10.5914 -11.6219 17.9362
hospbi*age_gr*sample B 6 1 A 6 3 0.5129 2.1133 30 0.24 0.8099 Tukey-Kramer 1.0000 0.05 -3.8030 4.8288 -8.0670 9.0927
hospbi*age_gr*sample B 6 1 B 6 3 -0.8328 2.2092 30 -0.38 0.7089 Tukey-Kramer 1.0000 0.05 -5.3445 3.6790 -9.8019 8.1364
hospbi*age_gr*sample B 6 1 C 6 3 -2.7264 2.4504 30 -1.11 0.2747 Tukey-Kramer 1.0000 0.05 -7.7308 2.2780 -12.6749 7.2221
hospbi*age_gr*sample B 6 1 A 9 1 -0.6665 2.3422 30 -0.28 0.7779 Tukey-Kramer 1.0000 0.05 -5.4500 4.1170 -10.1759 8.8429
hospbi*age_gr*sample B 6 1 B 9 1 0.3961 2.4923 30 0.16 0.8748 Tukey-Kramer 1.0000 0.05 -4.6938 5.4861 -9.7224 10.5147
hospbi*age_gr*sample B 6 1 C 9 1 0.07358 2.8598 30 0.03 0.9796 Tukey-Kramer 1.0000 0.05 -5.7669 5.9141 -11.5370 11.6842
hospbi*age_gr*sample B 6 1 A 9 2 1.6985 3.5535 30 0.48 0.6361 Tukey-Kramer 1.0000 0.05 -5.5587 8.9557 -12.7284 16.1255
hospbi*age_gr*sample B 6 1 B 9 2 2.3154 3.9407 30 0.59 0.5612 Tukey-Kramer 1.0000 0.05 -5.7325 10.3633 -13.6835 18.3142
hospbi*age_gr*sample B 6 1 C 9 2 0.1524 4.8370 30 0.03 0.9751 Tukey-Kramer 1.0000 0.05 -9.7261 10.0308 -19.4855 19.7903
hospbi*age_gr*sample B 6 1 A 9 3 -0.6310 2.0727 30 -0.30 0.7629 Tukey-Kramer 1.0000 0.05 -4.8640 3.6019 -9.0459 7.7839
hospbi*age_gr*sample B 6 1 B 9 3 -1.5589 2.1584 30 -0.72 0.4757 Tukey-Kramer 1.0000 0.05 -5.9670 2.8491 -10.3219 7.2040
hospbi*age_gr*sample B 6 1 C 9 3 -2.2383 2.3753 30 -0.94 0.3536 Tukey-Kramer 1.0000 0.05 -7.0893 2.6127 -11.8819 7.4053
hospbi*age_gr*sample C 6 1 A 6 2 2.4792 3.1358 30 0.79 0.4354 Tukey-Kramer 1.0000 0.05 -3.9250 8.8834 -10.2521 15.2105
hospbi*age_gr*sample C 6 1 B 6 2 2.8778 3.3592 30 0.86 0.3984 Tukey-Kramer 1.0000 0.05 -3.9826 9.7382 -10.7604 16.5159
hospbi*age_gr*sample C 6 1 C 6 2 2.7227 3.9010 30 0.70 0.4906 Tukey-Kramer 1.0000 0.05 -5.2442 10.6897 -13.1153 18.5607
hospbi*age_gr*sample C 6 1 A 6 3 0.07847 2.5363 30 0.03 0.9755 Tukey-Kramer 1.0000 0.05 -5.1014 5.2583 -10.2188 10.3758
hospbi*age_gr*sample C 6 1 B 6 3 -1.2671 2.6168 30 -0.48 0.6317 Tukey-Kramer 1.0000 0.05 -6.6113 4.0770 -11.8910 9.3567
hospbi*age_gr*sample C 6 1 C 6 3 -3.1608 2.8234 30 -1.12 0.2718 Tukey-Kramer 1.0000 0.05 -8.9268 2.6053 -14.6235 8.3019
hospbi*age_gr*sample C 6 1 A 9 1 -1.1009 2.7300 30 -0.40 0.6896 Tukey-Kramer 1.0000 0.05 -6.6763 4.4746 -12.1846 9.9829
hospbi*age_gr*sample C 6 1 B 9 1 -0.03826 2.8598 30 -0.01 0.9894 Tukey-Kramer 1.0000 0.05 -5.8787 5.8022 -11.6489 11.5724
hospbi*age_gr*sample C 6 1 C 9 1 -0.3608 3.1852 30 -0.11 0.9106 Tukey-Kramer 1.0000 0.05 -6.8658 6.1442 -13.2925 12.5709
hospbi*age_gr*sample C 6 1 A 9 2 1.2641 3.8202 30 0.33 0.7430 Tukey-Kramer 1.0000 0.05 -6.5378 9.0661 -14.2458 16.7741
hospbi*age_gr*sample C 6 1 B 9 2 1.8810 4.1828 30 0.45 0.6562 Tukey-Kramer 1.0000 0.05 -6.6614 10.4234 -15.1009 18.8629
hospbi*age_gr*sample C 6 1 C 9 2 -0.2820 5.0362 30 -0.06 0.9557 Tukey-Kramer 1.0000 0.05 -10.5673 10.0033 -20.7287 20.1647
hospbi*age_gr*sample C 6 1 A 9 3 -1.0654 2.5026 30 -0.43 0.6733 Tukey-Kramer 1.0000 0.05 -6.1763 4.0455 -11.2257 9.0949
hospbi*age_gr*sample C 6 1 B 9 3 -1.9933 2.5740 30 -0.77 0.4448 Tukey-Kramer 1.0000 0.05 -7.2502 3.2635 -12.4437 8.4570
hospbi*age_gr*sample C 6 1 C 9 3 -2.6727 2.7584 30 -0.97 0.3403 Tukey-Kramer 1.0000 0.05 -8.3062 2.9608 -13.8718 8.5265
hospbi*age_gr*sample A 6 2 B 6 2 0.3986 1.2980 30 0.31 0.7609 Tukey-Kramer 1.0000 0.05 -2.2523 3.0495 -4.8713 5.6685
hospbi*age_gr*sample A 6 2 C 6 2 0.2435 1.5515 30 0.16 0.8763 Tukey-Kramer 1.0000 0.05 -2.9251 3.4122 -6.0556 6.5427
hospbi*age_gr*sample A 6 2 A 6 3 -2.4007 2.4741 30 -0.97 0.3396 Tukey-Kramer 1.0000 0.05 -7.4534 2.6520 -12.4453 7.6438
hospbi*age_gr*sample A 6 2 B 6 3 -3.7463 2.5565 30 -1.47 0.1532 Tukey-Kramer 0.9985 0.05 -8.9673 1.4746 -14.1254 6.6327
hospbi*age_gr*sample A 6 2 C 6 3 -5.6400 2.7676 30 -2.04 0.0505 Tukey-Kramer 0.9328 0.05 -11.2921 0.01215 -16.8761 5.5962
hospbi*age_gr*sample A 6 2 A 9 1 -3.5801 2.6723 30 -1.34 0.1904 Tukey-Kramer 0.9996 0.05 -9.0376 1.8775 -14.4294 7.2693
hospbi*age_gr*sample A 6 2 B 9 1 -2.5175 2.8047 30 -0.90 0.3766 Tukey-Kramer 1.0000 0.05 -8.2455 3.2106 -13.9045 8.8696
hospbi*age_gr*sample A 6 2 C 9 1 -2.8400 3.1358 30 -0.91 0.3723 Tukey-Kramer 1.0000 0.05 -9.2442 3.5642 -15.5713 9.8913
hospbi*age_gr*sample A 6 2 A 9 2 -1.2151 3.7792 30 -0.32 0.7501 Tukey-Kramer 1.0000 0.05 -8.9332 6.5031 -16.5584 14.1282
hospbi*age_gr*sample A 6 2 B 9 2 -0.5982 4.1453 30 -0.14 0.8862 Tukey-Kramer 1.0000 0.05 -9.0641 7.8677 -17.4280 16.2316
hospbi*age_gr*sample A 6 2 C 9 2 -2.7612 5.0051 30 -0.55 0.5853 Tukey-Kramer 1.0000 0.05 -12.9831 7.4607 -23.0818 17.5594
hospbi*age_gr*sample A 6 2 A 9 3 -3.5446 2.4395 30 -1.45 0.1566 Tukey-Kramer 0.9987 0.05 -8.5266 1.4374 -13.4487 6.3595
hospbi*age_gr*sample A 6 2 B 9 3 -4.4725 2.5127 30 -1.78 0.0852 Tukey-Kramer 0.9824 0.05 -9.6041 0.6591 -14.6739 5.7289
hospbi*age_gr*sample A 6 2 C 9 3 -5.1519 2.7013 30 -1.91 0.0661 Tukey-Kramer 0.9638 0.05 -10.6687 0.3650 -16.1190 5.8153
hospbi*age_gr*sample B 6 2 C 6 2 -0.1551 1.1576 30 -0.13 0.8943 Tukey-Kramer 1.0000 0.05 -2.5192 2.2090 -4.8548 4.5447
hospbi*age_gr*sample B 6 2 A 6 3 -2.7993 2.7517 30 -1.02 0.3171 Tukey-Kramer 1.0000 0.05 -8.4190 2.8204 -13.9710 8.3723
hospbi*age_gr*sample B 6 2 B 6 3 -4.1449 2.8260 30 -1.47 0.1529 Tukey-Kramer 0.9985 0.05 -9.9164 1.6265 -15.6183 7.3284
hospbi*age_gr*sample B 6 2 C 6 3 -6.0386 3.0183 30 -2.00 0.0546 Tukey-Kramer 0.9430 0.05 -12.2028 0.1256 -18.2927 6.2156
hospbi*age_gr*sample B 6 2 A 9 1 -3.9786 2.9312 30 -1.36 0.1848 Tukey-Kramer 0.9995 0.05 -9.9649 2.0076 -15.8791 7.9218
hospbi*age_gr*sample B 6 2 B 9 1 -2.9160 3.0524 30 -0.96 0.3470 Tukey-Kramer 1.0000 0.05 -9.1499 3.3178 -15.3087 9.4766
hospbi*age_gr*sample B 6 2 C 9 1 -3.2386 3.3592 30 -0.96 0.3427 Tukey-Kramer 1.0000 0.05 -10.0990 3.6218 -16.8767 10.3996
hospbi*age_gr*sample B 6 2 A 9 2 -1.6137 3.9665 30 -0.41 0.6870 Tukey-Kramer 1.0000 0.05 -9.7143 6.4870 -17.7174 14.4901
hospbi*age_gr*sample B 6 2 B 9 2 -0.9968 4.3168 30 -0.23 0.8190 Tukey-Kramer 1.0000 0.05 -9.8128 7.8192 -18.5226 16.5291
hospbi*age_gr*sample B 6 2 C 9 2 -3.1598 5.1480 30 -0.61 0.5440 Tukey-Kramer 1.0000 0.05 -13.6735 7.3539 -24.0605 17.7410
hospbi*age_gr*sample B 6 2 A 9 3 -3.9432 2.7206 30 -1.45 0.1576 Tukey-Kramer 0.9987 0.05 -9.4994 1.6130 -14.9887 7.1023
hospbi*age_gr*sample B 6 2 B 9 3 -4.8711 2.7865 30 -1.75 0.0907 Tukey-Kramer 0.9856 0.05 -10.5618 0.8196 -16.1840 6.4418
hospbi*age_gr*sample B 6 2 C 9 3 -5.5504 2.9577 30 -1.88 0.0703 Tukey-Kramer 0.9692 0.05 -11.5908 0.4899 -17.5584 6.4576
hospbi*age_gr*sample C 6 2 A 6 3 -2.6442 3.3920 30 -0.78 0.4418 Tukey-Kramer 1.0000 0.05 -9.5716 4.2831 -16.4155 11.1270
hospbi*age_gr*sample C 6 2 B 6 3 -3.9899 3.4525 30 -1.16 0.2570 Tukey-Kramer 1.0000 0.05 -11.0409 3.0612 -18.0070 10.0273
hospbi*age_gr*sample C 6 2 C 6 3 -5.8835 3.6117 30 -1.63 0.1138 Tukey-Kramer 0.9938 0.05 -13.2595 1.4925 -20.5466 8.7796
hospbi*age_gr*sample C 6 2 A 9 1 -3.8236 3.5392 30 -1.08 0.2886 Tukey-Kramer 1.0000 0.05 -11.0515 3.4044 -18.1924 10.5453
hospbi*age_gr*sample C 6 2 B 9 1 -2.7610 3.6402 30 -0.76 0.4541 Tukey-Kramer 1.0000 0.05 -10.1953 4.6733 -17.5400 12.0181
hospbi*age_gr*sample C 6 2 C 9 1 -3.0835 3.9010 30 -0.79 0.4355 Tukey-Kramer 1.0000 0.05 -11.0505 4.8834 -18.9215 12.7545
hospbi*age_gr*sample C 6 2 A 9 2 -1.4586 4.4347 30 -0.33 0.7445 Tukey-Kramer 1.0000 0.05 -10.5155 7.5983 -19.4634 16.5462
hospbi*age_gr*sample C 6 2 B 9 2 -0.8417 4.7506 30 -0.18 0.8606 Tukey-Kramer 1.0000 0.05 -10.5438 8.8603 -20.1290 18.4455
hospbi*age_gr*sample C 6 2 C 9 2 -3.0047 5.5169 30 -0.54 0.5900 Tukey-Kramer 1.0000 0.05 -14.2717 8.2623 -25.4030 19.3936
hospbi*age_gr*sample C 6 2 A 9 3 -3.7881 3.3668 30 -1.13 0.2695 Tukey-Kramer 1.0000 0.05 -10.6641 3.0879 -17.4573 9.8810
hospbi*age_gr*sample C 6 2 B 9 3 -4.7161 3.4203 30 -1.38 0.1781 Tukey-Kramer 0.9994 0.05 -11.7012 2.2691 -18.6022 9.1701
hospbi*age_gr*sample C 6 2 C 9 3 -5.3954 3.5611 30 -1.52 0.1402 Tukey-Kramer 0.9976 0.05 -12.6682 1.8774 -19.8534 9.0626
hospbi*age_gr*sample A 6 3 B 6 3 -1.3456 0.6938 30 -1.94 0.0619 Tukey-Kramer 0.9573 0.05 -2.7626 0.07136 -4.1625 1.4713
hospbi*age_gr*sample A 6 3 C 6 3 -3.2392 0.8293 30 -3.91 0.0005 Tukey-Kramer 0.0709 0.05 -4.9330 -1.5455 -6.6063 0.1278
hospbi*age_gr*sample A 6 3 A 9 1 -1.1793 1.9341 30 -0.61 0.5466 Tukey-Kramer 1.0000 0.05 -5.1292 2.7705 -9.0315 6.6728
hospbi*age_gr*sample A 6 3 B 9 1 -0.1167 2.1133 30 -0.06 0.9563 Tukey-Kramer 1.0000 0.05 -4.4326 4.1992 -8.6965 8.4631
hospbi*age_gr*sample A 6 3 C 9 1 -0.4393 2.5363 30 -0.17 0.8637 Tukey-Kramer 1.0000 0.05 -5.6191 4.7406 -10.7366 9.8580
hospbi*age_gr*sample A 6 3 A 9 2 1.1857 3.2987 30 0.36 0.7218 Tukey-Kramer 1.0000 0.05 -5.5513 7.9226 -12.2071 14.5784
hospbi*age_gr*sample A 6 3 B 9 2 1.8025 3.7126 30 0.49 0.6308 Tukey-Kramer 1.0000 0.05 -5.7796 9.3846 -13.2703 16.8754
hospbi*age_gr*sample A 6 3 C 9 2 -0.3605 4.6531 30 -0.08 0.9388 Tukey-Kramer 1.0000 0.05 -9.8633 9.1423 -19.2516 18.5307
hospbi*age_gr*sample A 6 3 A 9 3 -1.1439 1.5970 30 -0.72 0.4794 Tukey-Kramer 1.0000 0.05 -4.4054 2.1176 -7.6276 5.3399
hospbi*age_gr*sample A 6 3 B 9 3 -2.0718 1.7068 30 -1.21 0.2343 Tukey-Kramer 0.9999 0.05 -5.5575 1.4139 -9.0012 4.8576
hospbi*age_gr*sample A 6 3 C 9 3 -2.7511 1.9740 30 -1.39 0.1736 Tukey-Kramer 0.9993 0.05 -6.7825 1.2802 -10.7653 5.2631
hospbi*age_gr*sample B 6 3 C 6 3 -1.8936 0.6188 30 -3.06 0.0046 Tukey-Kramer 0.3604 0.05 -3.1573 -0.6300 -4.4057 0.6185
hospbi*age_gr*sample B 6 3 A 9 1 0.1663 2.0384 30 0.08 0.9355 Tukey-Kramer 1.0000 0.05 -3.9967 4.3293 -8.1095 8.4421
hospbi*age_gr*sample B 6 3 B 9 1 1.2289 2.2092 30 0.56 0.5822 Tukey-Kramer 1.0000 0.05 -3.2829 5.7406 -7.7403 10.1980
hospbi*age_gr*sample B 6 3 C 9 1 0.9063 2.6168 30 0.35 0.7315 Tukey-Kramer 1.0000 0.05 -4.4378 6.2505 -9.7175 11.5302
hospbi*age_gr*sample B 6 3 A 9 2 2.5313 3.3610 30 0.75 0.4572 Tukey-Kramer 1.0000 0.05 -4.3328 9.3953 -11.1141 16.1767
hospbi*age_gr*sample B 6 3 B 9 2 3.1481 3.7680 30 0.84 0.4100 Tukey-Kramer 1.0000 0.05 -4.5471 10.8434 -12.1497 18.4460
hospbi*age_gr*sample B 6 3 C 9 2 0.9851 4.6974 30 0.21 0.8353 Tukey-Kramer 1.0000 0.05 -8.6082 10.5785 -18.0860 20.0563
hospbi*age_gr*sample B 6 3 A 9 3 0.2017 1.7219 30 0.12 0.9075 Tukey-Kramer 1.0000 0.05 -3.3148 3.7183 -6.7890 7.1925
hospbi*age_gr*sample B 6 3 B 9 3 -0.7262 1.8242 30 -0.40 0.6934 Tukey-Kramer 1.0000 0.05 -4.4516 2.9993 -8.1322 6.6798
hospbi*age_gr*sample B 6 3 C 9 3 -1.4055 2.0763 30 -0.68 0.5036 Tukey-Kramer 1.0000 0.05 -5.6459 2.8349 -9.8352 7.0242
hospbi*age_gr*sample C 6 3 A 9 1 2.0599 2.2976 30 0.90 0.3771 Tukey-Kramer 1.0000 0.05 -2.6324 6.7523 -7.2683 11.3881
hospbi*age_gr*sample C 6 3 B 9 1 3.1225 2.4504 30 1.27 0.2123 Tukey-Kramer 0.9998 0.05 -1.8818 8.1269 -6.8259 13.0710
hospbi*age_gr*sample C 6 3 C 9 1 2.8000 2.8234 30 0.99 0.3293 Tukey-Kramer 1.0000 0.05 -2.9661 8.5660 -8.6627 14.2627
hospbi*age_gr*sample C 6 3 A 9 2 4.4249 3.5242 30 1.26 0.2190 Tukey-Kramer 0.9999 0.05 -2.7725 11.6223 -9.8833 18.7331
hospbi*age_gr*sample C 6 3 B 9 2 5.0418 3.9143 30 1.29 0.2076 Tukey-Kramer 0.9998 0.05 -2.9523 13.0358 -10.8500 20.9336
hospbi*age_gr*sample C 6 3 C 9 2 2.8788 4.8155 30 0.60 0.5545 Tukey-Kramer 1.0000 0.05 -6.9559 12.7134 -16.6720 22.4296
hospbi*age_gr*sample C 6 3 A 9 3 2.0954 2.0221 30 1.04 0.3084 Tukey-Kramer 1.0000 0.05 -2.0343 6.2250 -6.1142 10.3050
hospbi*age_gr*sample C 6 3 B 9 3 1.1674 2.1099 30 0.55 0.5841 Tukey-Kramer 1.0000 0.05 -3.1415 5.4764 -7.3985 9.7334
hospbi*age_gr*sample C 6 3 C 9 3 0.4881 2.3313 30 0.21 0.8356 Tukey-Kramer 1.0000 0.05 -4.2731 5.2493 -8.9769 9.9531
hospbi*age_gr*sample A 9 1 B 9 1 1.0626 0.9178 30 1.16 0.2561 Tukey-Kramer 1.0000 0.05 -0.8119 2.9371 -2.6638 4.7890
hospbi*age_gr*sample A 9 1 C 9 1 0.7401 1.0971 30 0.67 0.5051 Tukey-Kramer 1.0000 0.05 -1.5005 2.9806 -3.7141 5.1942
hospbi*age_gr*sample A 9 1 A 9 2 2.3650 3.4499 30 0.69 0.4983 Tukey-Kramer 1.0000 0.05 -4.6807 9.4107 -11.6414 16.3714
hospbi*age_gr*sample A 9 1 B 9 2 2.9819 3.8475 30 0.78 0.4444 Tukey-Kramer 1.0000 0.05 -4.8758 10.8395 -12.6388 18.6026
hospbi*age_gr*sample A 9 1 C 9 2 0.8189 4.7614 30 0.17 0.8646 Tukey-Kramer 1.0000 0.05 -8.9052 10.5430 -18.5122 20.1500
hospbi*age_gr*sample A 9 1 A 9 3 0.03546 1.8896 30 0.02 0.9851 Tukey-Kramer 1.0000 0.05 -3.8236 3.8945 -7.6362 7.7071
hospbi*age_gr*sample A 9 1 B 9 3 -0.8925 1.9832 30 -0.45 0.6559 Tukey-Kramer 1.0000 0.05 -4.9428 3.1579 -8.9443 7.1594
hospbi*age_gr*sample A 9 1 C 9 3 -1.5718 2.2174 30 -0.71 0.4839 Tukey-Kramer 1.0000 0.05 -6.1003 2.9567 -10.5742 7.4306
hospbi*age_gr*sample B 9 1 C 9 1 -0.3225 0.8185 30 -0.39 0.6963 Tukey-Kramer 1.0000 0.05 -1.9942 1.3491 -3.6457 3.0007
hospbi*age_gr*sample B 9 1 A 9 2 1.3024 3.5535 30 0.37 0.7166 Tukey-Kramer 1.0000 0.05 -5.9548 8.5596 -13.1246 15.7294
hospbi*age_gr*sample B 9 1 B 9 2 1.9193 3.9407 30 0.49 0.6298 Tukey-Kramer 1.0000 0.05 -6.1286 9.9671 -14.0796 17.9181
hospbi*age_gr*sample B 9 1 C 9 2 -0.2437 4.8370 30 -0.05 0.9601 Tukey-Kramer 1.0000 0.05 -10.1222 9.6347 -19.8817 19.3942
hospbi*age_gr*sample B 9 1 A 9 3 -1.0271 2.0727 30 -0.50 0.6238 Tukey-Kramer 1.0000 0.05 -5.2601 3.2058 -9.4420 7.3878
hospbi*age_gr*sample B 9 1 B 9 3 -1.9551 2.1584 30 -0.91 0.3723 Tukey-Kramer 1.0000 0.05 -6.3631 2.4529 -10.7180 6.8079
hospbi*age_gr*sample B 9 1 C 9 3 -2.6344 2.3753 30 -1.11 0.2762 Tukey-Kramer 1.0000 0.05 -7.4854 2.2166 -12.2780 7.0092
hospbi*age_gr*sample C 9 1 A 9 2 1.6249 3.8202 30 0.43 0.6736 Tukey-Kramer 1.0000 0.05 -6.1770 9.4269 -13.8850 17.1349
hospbi*age_gr*sample C 9 1 B 9 2 2.2418 4.1828 30 0.54 0.5959 Tukey-Kramer 1.0000 0.05 -6.3006 10.7842 -14.7401 19.2237
hospbi*age_gr*sample C 9 1 C 9 2 0.07880 5.0362 30 0.02 0.9876 Tukey-Kramer 1.0000 0.05 -10.2065 10.3641 -20.3679 20.5255
hospbi*age_gr*sample C 9 1 A 9 3 -0.7046 2.5026 30 -0.28 0.7802 Tukey-Kramer 1.0000 0.05 -5.8155 4.4063 -10.8649 9.4557
hospbi*age_gr*sample C 9 1 B 9 3 -1.6325 2.5740 30 -0.63 0.5307 Tukey-Kramer 1.0000 0.05 -6.8894 3.6243 -12.0829 8.8178
hospbi*age_gr*sample C 9 1 C 9 3 -2.3119 2.7584 30 -0.84 0.4086 Tukey-Kramer 1.0000 0.05 -7.9454 3.3216 -13.5110 8.8873
hospbi*age_gr*sample A 9 2 B 9 2 0.6169 1.8357 30 0.34 0.7392 Tukey-Kramer 1.0000 0.05 -3.1321 4.3658 -6.8359 8.0696
hospbi*age_gr*sample A 9 2 C 9 2 -1.5461 2.1942 30 -0.70 0.4865 Tukey-Kramer 1.0000 0.05 -6.0273 2.9350 -10.4545 7.3622
hospbi*age_gr*sample A 9 2 A 9 3 -2.3295 3.2729 30 -0.71 0.4821 Tukey-Kramer 1.0000 0.05 -9.0136 4.3546 -15.6172 10.9581
hospbi*age_gr*sample A 9 2 B 9 3 -3.2575 3.3278 30 -0.98 0.3355 Tukey-Kramer 1.0000 0.05 -10.0538 3.5388 -16.7682 10.2533
hospbi*age_gr*sample A 9 2 C 9 3 -3.9368 3.4724 30 -1.13 0.2659 Tukey-Kramer 1.0000 0.05 -11.0285 3.1549 -18.0347 10.1611
hospbi*age_gr*sample B 9 2 C 9 2 -2.1630 1.6371 30 -1.32 0.1964 Tukey-Kramer 0.9997 0.05 -5.5063 1.1803 -8.8094 4.4834
hospbi*age_gr*sample B 9 2 A 9 3 -2.9464 3.6896 30 -0.80 0.4308 Tukey-Kramer 1.0000 0.05 -10.4816 4.5888 -17.9260 12.0332
hospbi*age_gr*sample B 9 2 B 9 3 -3.8743 3.7384 30 -1.04 0.3083 Tukey-Kramer 1.0000 0.05 -11.5092 3.7606 -19.0522 11.3035
hospbi*age_gr*sample B 9 2 C 9 3 -4.5537 3.8677 30 -1.18 0.2483 Tukey-Kramer 1.0000 0.05 -12.4526 3.3453 -20.2564 11.1491
hospbi*age_gr*sample C 9 2 A 9 3 -0.7834 4.6347 30 -0.17 0.8669 Tukey-Kramer 1.0000 0.05 -10.2488 8.6820 -19.6002 18.0334
hospbi*age_gr*sample C 9 2 B 9 3 -1.7113 4.6737 30 -0.37 0.7168 Tukey-Kramer 1.0000 0.05 -11.2563 7.8337 -20.6864 17.2637
hospbi*age_gr*sample C 9 2 C 9 3 -2.3907 4.7778 30 -0.50 0.6205 Tukey-Kramer 1.0000 0.05 -12.1482 7.3668 -21.7881 17.0068
hospbi*age_gr*sample A 9 3 B 9 3 -0.9279 0.6490 30 -1.43 0.1631 Tukey-Kramer 0.9989 0.05 -2.2534 0.3975 -3.5629 1.7070
hospbi*age_gr*sample A 9 3 C 9 3 -1.6073 0.7758 30 -2.07 0.0470 Tukey-Kramer 0.9225 0.05 -3.1916 -0.02293 -4.7568 1.5423
hospbi*age_gr*sample B 9 3 C 9 3 -0.6793 0.5788 30 -1.17 0.2497 Tukey-Kramer 1.0000 0.05 -1.8614 0.5027 -3.0292 1.6705

Data for supplemental table 2 and Figure 1

In [11]:
/*ls means values by head body and tail*/

DATA cd45_lsmeans1 (drop=age_group);
     set cd45_lsmeans;
     if age_group^="" then delete;
     stain="CD45           ";
     rename _NAME_=pancreas_region;
run;

PROC print data=cd45_lsmeans1;
run;

/*grand mean values*/

PROC means data=cd45_lsmeans1 mean;
     var lsmean;
     class hospbin;
     output out=cd45_grandmean;
run;

DATA cd45_grandmean (drop=_type_ _freq_ _stat_);
     set cd45_grandmean;
     if _stat_^="MEAN" then delete;
     if hospbin="" then delete;
     pancreas_region="Overall";
     stain="CD45           ";
run;

/*combine files into 1*/

DATA cd45_fig1;
     set cd45_lsmeans1 cd45_grandmean;
run;

PROC print data=cd45_fig1;
run;
Out[11]:
SAS Output

The SAS System

Obs pancreas_region hospbin LSMEAN stain
1 Head 3 3.97633 CD45
2 Head 6 3.64362 CD45
3 Head 9 4.86435 CD45
4 Body 3 4.21742 CD45
5 Body 6 4.17156 CD45
6 Body 9 4.61384 CD45
7 Tail 3 5.35137 CD45
8 Tail 6 4.70966 CD45
9 Tail 9 5.66880 CD45

The SAS System

The MEANS Procedure

Analysis Variable : LSMEAN
hospbin N Obs Mean
3 3 4.5150417
6 3 4.1749456
9 3 5.0489974

The SAS System

Obs pancreas_region hospbin LSMEAN stain
1 Head 3 3.97633 CD45
2 Head 6 3.64362 CD45
3 Head 9 4.86435 CD45
4 Body 3 4.21742 CD45
5 Body 6 4.17156 CD45
6 Body 9 4.61384 CD45
7 Tail 3 5.35137 CD45
8 Tail 6 4.70966 CD45
9 Tail 9 5.66880 CD45
10 Overall 3 4.51504 CD45
11 Overall 6 4.17495 CD45
12 Overall 9 5.04900 CD45

Data for figure 2

Figure 2A generation

In [12]:
/*boxplots of staining levels grouped by panc region*/

PROC sort data=cd45;
    by sample_type2;
run;

PROC means data=cd45 mean std median min max;
     var percent_cd45;
     by sample_type2;
run;

DATA long_cd45;
     set cd45;
     stain="CD45     ";
     percent_cells=percent_cd45;
output;

     stain="Insulin";
        percent_cells=percent_insulin;
output;

     stain="Negative";
     percent_cells=percent_negative;
output;

     drop percent_cd45 percent_insulin percent_negative;
run;
Out[12]:
SAS Output

The SAS System

The MEANS Procedure

Analysis Variable : percent_cd45 %% CD45 Positive Cells
Mean Std Dev Median Minimum Maximum
4.4040423 2.9356949 3.6430000 0.4548470 12.3875000
Analysis Variable : percent_cd45 %% CD45 Positive Cells
Mean Std Dev Median Minimum Maximum
4.8285966 3.4253421 4.1014500 0.4878000 16.1682000
Analysis Variable : percent_cd45 %% CD45 Positive Cells
Mean Std Dev Median Minimum Maximum
5.6485486 4.3681732 4.5529300 0.5273950 18.4238000
In [13]:
ODS GRAPHICS ON / reset = all height= 4 in width=7 in border= off imagename="Fig2A";
ods listing image_dpi=600;

PROC sgplot data=long_cd45 (where=(stain = 'CD45')) noautolegend;
     format sample_type2 $pancorder.;
     styleattrs datacolors=(white) datacontrastcolors=(black);
     scatter x=sample_type2 y=percent_cells/ group=stain name="Circles" jitter MARKERATTRS=(symbol=circle size=10) MARKEROUTLINEATTRS=(thickness=1) transparency=0.4;
     vbox percent_cells / whiskerpct=5 /*95% percentile*/ category=sample_type2 group=stain transparency=0.50 meanattrs=(color=black symbol=circlefilled size=14) fillattrs=(color=white transparency=.5);
     yaxis grid;
     xaxis discreteorder=data labelattrs=(size=18) valueattrs=(size=18) label="Pancreas region" labelattrs=(size = 19 Family=Arial weight=bold);
     
     yaxis values=(0 to 20 by 5) labelattrs=(size=18) valueattrs=(size=18) label="CD45+ cells (% total)" labelattrs = (size = 19 Family=Arial weight=bold);
     inset /title= "a" titleattrs=(size=19) titleattrs=(weight=bold) position=topright noborder;
run;

ODS GRAPHICS off;
Out[13]:
SAS Output
The SGPlot Procedure

Figure 2B generation. Code for figure adapoted from Robin High, University of Nebraska Medical Center and is available here.

In [14]:
/*need to prepare data file*/

DATA differences (drop=hospbin _hospbin age_group _age_group);
     format sample_type2 $pancorder. _sample_type2 $pancorder.;
     set cd45_lsmeans_diff;
     if effect^="sample_type2" then delete;
     if sample_type2="A" then region1="Head";
     if sample_type2="B" then region1="Body";
     if sample_type2="C" then region1="Tail";
     if _sample_type2="A" then region2="Head";
     if _sample_type2="B" then region2="Body";
     if _sample_type2="C" then region2="Tail";
run;

PROC print data=differences;
run;
Out[14]:
SAS Output

The SAS System

Obs sample_type2 _sample_type2 Effect Estimate StdErr DF tValue Probt Adjustment Adjp Alpha Lower Upper AdjLower AdjUpper region1 region2
1 Head Body sample_type2 -0.1728 0.3664 30 -0.47 0.6405 Tukey-Kramer 0.8850 0.05 -0.9210 0.5754 -1.0760 0.7303 Head Body
2 Head Tail sample_type2 -1.0818 0.4379 30 -2.47 0.0194 Tukey-Kramer 0.0494 0.05 -1.9762 -0.1875 -2.1614 -0.00230 Head Tail
3 Body Tail sample_type2 -0.9090 0.3267 30 -2.78 0.0092 Tukey-Kramer 0.0244 0.05 -1.5762 -0.2418 -1.7144 -0.1036 Body Tail
In [15]:
/* Forest Plot of Differences 
with the file of differences add a text variable called label describing each comparison;*/
DATA dfs2;
     SET differences (rename=(estimate=mndif1 adjlower=adjlower1 adjupper=adjupper1));
     DROP ptxt;
     LENGTH label $30 ptxt $4;
     IF pvalue < .001 then ptxt=', p='; else ptxt=', p=';
     label = CAT(put(region1,4.),' vs ',
     put(region2,4.));
     * new variables for non-significant differences, set existing to missing;
     IF (pvalue GE 0.05) then do;
     mndif2 = mndif1; adjlower2 = adjlower1; adjupper2 =adjupper1;
     mndif1 = . ; adjlower1 = . ; adjupper1 = . ;
     end;
RUN;

PROC print data=dfs2;
run;

ODS GRAPHICS ON / reset = all height= 4 in width=7 in border= off imagename="Fig2B";
ods listing image_dpi=600;

PROC sgplot data=dfs2 noautolegend;
     REFLINE 0 / axis=x lineattrs=(color=black pattern=2 thickness=1) transparency=0;
     
     SCATTER y=label x=mndif1 / xerrorlower=adjlower1 xerrorupper=adjupper1
     errorbarattrs=(color=black pattern=1 thickness=2)
     markerattrs=(color=black symbol= circlefilled size=16)
     datalabel=mndif1 datalabelattrs=(color=black size=16) y2axis;
     
     /* print the differences at the center of each confidence interval */
     
     SCATTER y=label x=mndif2 / xerrorlower=adjlower2 xerrorupper=adjupper2
     
     markerattrs=(color=black symbol= circlefilled size=16)
     datalabel=mndif2 datalabelattrs=(color=black size=16) y2axis;
     
     XAXIS offsetmin=0.05 offsetmax=0.05 label='Differences and Adjusted 95% CI' labelattrs=(size = 18 Family=Arial weight=bold) values=(-3 to 1 by 1) valueattrs=(size=18);
     Y2AXIS offsetmin=0.12 offsetmax=0.12 display=(Nolabel Noticks) reverse labelattrs=(size=18) valueattrs=(size=18);
     
     inset /title= "b" titleattrs=(size=18) titleattrs=(weight=bold) position=topright noborder;
     FORMAT mndif1 mndif2 5.2;
     title ;
run;

ODS GRAPHICS off;
Out[15]:
SAS Output

The SAS System

Obs sample_type2 _sample_type2 Effect mndif1 StdErr DF tValue Probt Adjustment Adjp Alpha Lower Upper adjlower1 adjupper1 region1 region2 label pvalue mndif2 adjlower2 adjupper2
1 Head Body sample_type2 -0.1728 0.3664 30 -0.47 0.6405 Tukey-Kramer 0.8850 0.05 -0.9210 0.5754 -1.0760 0.7303 Head Body Head vs Body . . . .
2 Head Tail sample_type2 -1.0818 0.4379 30 -2.47 0.0194 Tukey-Kramer 0.0494 0.05 -1.9762 -0.1875 -2.1614 -0.00230 Head Tail Head vs Tail . . . .
3 Body Tail sample_type2 -0.9090 0.3267 30 -2.78 0.0092 Tukey-Kramer 0.0244 0.05 -1.5762 -0.2418 -1.7144 -0.1036 Body Tail Body vs Tail . . . .

The SGPlot Procedure

To combine 2a and 2b into one figure, take png files and combine in inkscape at 1100mm width, 379mm height, 600 dpi. From there, use online image converter to change from png to eps.

CD68 dataset

statistical analysis model

In [16]:
PROC glm data=cd68_no_insulin;
     class hospbin age_group;
     model Head Body Tail= hospbin|age_group/nouni; 
     repeated sample_type2 / short printe; 
     lsmeans hospbin|age_group /out=cd68_lsmeans (drop=stderr);
run;
quit;

PROC mixed data=cd68;
     class case hospbin age_group sample_type2;
     model percent_cd68=hospbin|age_group|sample_type2;
     repeated sample_type2/ subject=case(hospbin) type=un;
     lsmeans hospbin|age_group|sample_type2 /adjust=tukey cl pdiff alpha=0.05;
run;
Out[16]:
SAS Output

The GLM Procedure

Class Level Information
Class Levels Values
hospbin 3 3 6 9
age_group 3 1 2 3
Number of Observations Read 39
Number of Observations Used 39

The GLM Procedure

Repeated Measures Analysis of Variance

Repeated Measures Level Information
Dependent Variable Head Body Tail
Level of sample_type2 1 2 3
Partial Correlation Coefficients from the Error SSCP Matrix / Prob > |r|
DF = 30 Head Body Tail
Head
1.000000
 
0.862037
<.0001
0.909662
<.0001
Body
0.862037
<.0001
1.000000
 
0.872630
<.0001
Tail
0.909662
<.0001
0.872630
<.0001
1.000000
 
E = Error SSCP Matrix

sample_type2_N represents the contrast between the nth level of sample_type2 and the last
  sample_type2_1 sample_type2_2
sample_type2_1 50.151 32.616
sample_type2_2 32.616 65.805
Partial Correlation Coefficients from the Error SSCP Matrix of the Variables Defined by the Specified Transformation / Prob > |r|
DF = 30 sample_type2_1 sample_type2_2
sample_type2_1
1.000000
 
0.567753
0.0009
sample_type2_2
0.567753
0.0009
1.000000
 
Sphericity Tests
Variables DF Mauchly's Criterion Chi-Square Pr > ChiSq
Transformed Variates 2 0.6653069 11.817699 0.0027
Orthogonal Components 2 0.9659646 1.0042133 0.6053
MANOVA Test Criteria and Exact F Statistics for the Hypothesis of no sample_type2 Effect
H = Type III SSCP Matrix for sample_type2
E = Error SSCP Matrix

S=1 M=0 N=13.5
Statistic Value F Value Num DF Den DF Pr > F
Wilks' Lambda 0.89505139 1.70 2 29 0.2004
Pillai's Trace 0.10494861 1.70 2 29 0.2004
Hotelling-Lawley Trace 0.11725429 1.70 2 29 0.2004
Roy's Greatest Root 0.11725429 1.70 2 29 0.2004
MANOVA Test Criteria and F Approximations for the Hypothesis of no sample_type2*hospbin Effect
H = Type III SSCP Matrix for sample_type2*hospbin
E = Error SSCP Matrix

S=2 M=-0.5 N=13.5
Statistic Value F Value Num DF Den DF Pr > F
NOTE: F Statistic for Roy's Greatest Root is an upper bound.
NOTE: F Statistic for Wilks' Lambda is exact.
Wilks' Lambda 0.91997142 0.62 4 58 0.6518
Pillai's Trace 0.08093707 0.63 4 60 0.6412
Hotelling-Lawley Trace 0.08600276 0.62 4 33.787 0.6534
Roy's Greatest Root 0.07235429 1.09 2 30 0.3507
MANOVA Test Criteria and F Approximations for the Hypothesis of no sample_type2*age_group Effect
H = Type III SSCP Matrix for sample_type2*age_group
E = Error SSCP Matrix

S=2 M=-0.5 N=13.5
Statistic Value F Value Num DF Den DF Pr > F
NOTE: F Statistic for Roy's Greatest Root is an upper bound.
NOTE: F Statistic for Wilks' Lambda is exact.
Wilks' Lambda 0.90093548 0.78 4 58 0.5451
Pillai's Trace 0.10038169 0.79 4 60 0.5346
Hotelling-Lawley Trace 0.10849539 0.78 4 33.787 0.5471
Roy's Greatest Root 0.09272899 1.39 2 30 0.2644
MANOVA Test Criteria and F Approximations for the Hypothesis of no sample_type2*hospbin*age_group Effect
H = Type III SSCP Matrix for sample_type2*hospbin*age_group
E = Error SSCP Matrix

S=2 M=0.5 N=13.5
Statistic Value F Value Num DF Den DF Pr > F
NOTE: F Statistic for Roy's Greatest Root is an upper bound.
NOTE: F Statistic for Wilks' Lambda is exact.
Wilks' Lambda 0.70965461 1.36 8 58 0.2351
Pillai's Trace 0.30564435 1.35 8 60 0.2358
Hotelling-Lawley Trace 0.38757788 1.38 8 39.176 0.2361
Roy's Greatest Root 0.32026359 2.40 4 30 0.0719

The GLM Procedure

Repeated Measures Analysis of Variance

Tests of Hypotheses for Between Subjects Effects

Source DF Type III SS Mean Square F Value Pr > F
hospbin 2 15.4217801 7.7108901 0.40 0.6768
age_group 2 5.7086161 2.8543080 0.15 0.8644
hospbin*age_group 4 84.5180004 21.1295001 1.08 0.3822
Error 30 584.9659330 19.4988644    

The GLM Procedure

Repeated Measures Analysis of Variance

Univariate Tests of Hypotheses for Within Subject Effects

Source DF Type III SS Mean Square F Value Pr > F Adj Pr > F
G - G H-F-L
sample_type2 2 2.73498881 1.36749440 1.48 0.2366 0.2370 0.2366
sample_type2*hospbin 4 2.35829187 0.58957297 0.64 0.6383 0.6333 0.6383
sample_type2*age_group 4 2.72728578 0.68182145 0.74 0.5709 0.5668 0.5709
sample_type2*hospbin*age_group 8 9.50018091 1.18752261 1.28 0.2698 0.2717 0.2698
Error(sample_type2) 60 55.56024159 0.92600403        
Greenhouse-Geisser Epsilon 0.9671
Huynh-Feldt-Lecoutre Epsilon 1.0326

The GLM Procedure

Least Squares Means

hospbin Head LSMEAN
3 2.11728685
6 2.11608285
9 3.43758125
Plot of Head least-squares means for hospbin.
hospbin Body LSMEAN
3 2.81909324
6 2.58785874
9 3.18991917
Plot of Body least-squares means for hospbin.
hospbin Tail LSMEAN
3 2.81955772
6 2.41700594
9 3.80707425
Plot of Tail least-squares means for hospbin.
age_group Head LSMEAN
1 3.13823031
2 2.02036300
3 2.51235764
Plot of Head least-squares means for age_group.
age_group Body LSMEAN
1 3.08226794
2 2.61529383
3 2.89930936
Plot of Body least-squares means for age_group.
age_group Tail LSMEAN
1 3.21079489
2 2.47398517
3 3.35885786
Plot of Tail least-squares means for age_group.
hospbin age_group Head LSMEAN
3 1 1.62014067
3 2 3.27999250
3 3 1.45172738
6 1 2.66193775
6 2 1.10180650
6 3 2.58450429
9 1 5.13261250
9 2 1.67929000
9 3 3.50084125
Plot of Head least-squares means for hospbin*age_group.
hospbin age_group Body LSMEAN
3 1 1.78869133
3 2 5.22790350
3 3 1.44068488
6 1 3.36748250
6 2 1.00343800
6 3 3.39265571
9 1 4.09063000
9 2 1.61454000
9 3 3.86458750
Plot of Body least-squares means for hospbin*age_group.
hospbin age_group Tail LSMEAN
3 1 1.74930567
3 2 5.00996250
3 3 1.69940500
6 1 2.90622625
6 2 1.35808300
6 3 2.98670857
9 1 4.97685275
9 2 1.05391000
9 3 5.39046000
Plot of Tail least-squares means for hospbin*age_group.

The Mixed Procedure

Model Information
Data Set WORK.CD68
Dependent Variable percent_cd68
Covariance Structure Unstructured
Subject Effect Case(hospbin)
Estimation Method REML
Residual Variance Method None
Fixed Effects SE Method Model-Based
Degrees of Freedom Method Between-Within
Class Level Information
Class Levels Values
Case 39 6003 6005 6007 6008 6011 6019 6047 6048 6057 6060 6073 6099 6104 6106 6115 6117 6126 6129 6131 6134 6140 6144 6162 6165 6172 6174 6178 6179 6187 6200 6219 6229 6230 6235 6250 6251 6254 6278 6279
hospbin 3 3 6 9
age_group 3 1 2 3
sample_type2 3 A B C
Dimensions
Covariance Parameters 6
Columns in X 64
Columns in Z 0
Subjects 39
Max Obs per Subject 3
Number of Observations
Number of Observations Read 117
Number of Observations Used 117
Number of Observations Not Used 0
Iteration History
Iteration Evaluations -2 Res Log Like Criterion
0 1 466.11903024  
1 1 365.10229756 0.00000000
Convergence criteria met.
Covariance Parameter Estimates
Cov Parm Subject Estimate
UN(1,1) Case(hospbin) 5.9362
UN(2,1) Case(hospbin) 5.2666
UN(2,2) Case(hospbin) 6.2878
UN(3,1) Case(hospbin) 6.6957
UN(3,2) Case(hospbin) 6.6106
UN(3,3) Case(hospbin) 9.1269
Fit Statistics
-2 Res Log Likelihood 365.1
AIC (Smaller is Better) 377.1
AICC (Smaller is Better) 378.1
BIC (Smaller is Better) 387.1
Null Model Likelihood Ratio Test
DF Chi-Square Pr > ChiSq
5 101.02 <.0001
Type 3 Tests of Fixed Effects
Effect Num DF Den DF F Value Pr > F
hospbin 2 30 0.40 0.6768
age_group 2 30 0.15 0.8644
hospbin*age_group 4 30 1.08 0.3822
sample_type2 2 30 1.76 0.1895
hospbin*sample_type2 4 30 0.65 0.6347
age_group*sample_typ 4 30 0.81 0.5265
hospbi*age_gr*sample 8 30 1.45 0.2158
Least Squares Means
Effect sample_type2 hospbin age_group Estimate Standard
Error
DF t Value Pr > |t| Alpha Lower Upper
hospbin   3   2.5853 0.8319 30 3.11 0.0041 0.05 0.8863 4.2843
hospbin   6   2.3736 0.8030 30 2.96 0.0060 0.05 0.7337 4.0136
hospbin   9   3.4782 0.9965 30 3.49 0.0015 0.05 1.4431 5.5133
age_group     1 3.1438 0.7758 30 4.05 0.0003 0.05 1.5594 4.7281
age_group     2 2.3699 1.2018 30 1.97 0.0579 0.05 -0.08455 4.8243
age_group     3 2.9235 0.5326 30 5.49 <.0001 0.05 1.8357 4.0113
hospbin*age_group   3 1 1.7194 1.4719 30 1.17 0.2520 0.05 -1.2867 4.7254
hospbin*age_group   3 2 4.5060 1.8027 30 2.50 0.0181 0.05 0.8243 8.1876
hospbin*age_group   3 3 1.5306 0.9014 30 1.70 0.0998 0.05 -0.3102 3.3714
hospbin*age_group   6 1 2.9785 1.2747 30 2.34 0.0263 0.05 0.3752 5.5819
hospbin*age_group   6 2 1.1544 1.8027 30 0.64 0.5268 0.05 -2.5272 4.8361
hospbin*age_group   6 3 2.9880 0.9636 30 3.10 0.0042 0.05 1.0200 4.9559
hospbin*age_group   9 1 4.7334 1.2747 30 3.71 0.0008 0.05 2.1300 7.3367
hospbin*age_group   9 2 1.4492 2.5494 30 0.57 0.5740 0.05 -3.7574 6.6559
hospbin*age_group   9 3 4.2520 0.9014 30 4.72 <.0001 0.05 2.4111 6.0928
sample_type2 A     2.5570 0.4862 30 5.26 <.0001 0.05 1.5639 3.5500
sample_type2 B     2.8656 0.5004 30 5.73 <.0001 0.05 1.8436 3.8877
sample_type2 C     3.0145 0.6029 30 5.00 <.0001 0.05 1.7832 4.2459
hospbin*sample_type2 A 3   2.1173 0.7950 30 2.66 0.0123 0.05 0.4936 3.7410
hospbin*sample_type2 B 3   2.8191 0.8182 30 3.45 0.0017 0.05 1.1480 4.4902
hospbin*sample_type2 C 3   2.8196 0.9858 30 2.86 0.0076 0.05 0.8062 4.8329
hospbin*sample_type2 A 6   2.1161 0.7674 30 2.76 0.0098 0.05 0.5488 3.6833
hospbin*sample_type2 B 6   2.5879 0.7898 30 3.28 0.0027 0.05 0.9749 4.2008
hospbin*sample_type2 C 6   2.4170 0.9516 30 2.54 0.0165 0.05 0.4737 4.3603
hospbin*sample_type2 A 9   3.4376 0.9523 30 3.61 0.0011 0.05 1.4927 5.3825
hospbin*sample_type2 B 9   3.1899 0.9801 30 3.25 0.0028 0.05 1.1882 5.1916
hospbin*sample_type2 C 9   3.8071 1.1808 30 3.22 0.0030 0.05 1.3955 6.2187
age_group*sample_typ A   1 3.1382 0.7414 30 4.23 0.0002 0.05 1.6241 4.6523
age_group*sample_typ B   1 3.0823 0.7630 30 4.04 0.0003 0.05 1.5240 4.6406
age_group*sample_typ C   1 3.2108 0.9193 30 3.49 0.0015 0.05 1.3334 5.0882
age_group*sample_typ A   2 2.0204 1.1485 30 1.76 0.0888 0.05 -0.3253 4.3660
age_group*sample_typ B   2 2.6153 1.1821 30 2.21 0.0347 0.05 0.2012 5.0294
age_group*sample_typ C   2 2.4740 1.4242 30 1.74 0.0926 0.05 -0.4345 5.3825
age_group*sample_typ A   3 2.5124 0.5090 30 4.94 <.0001 0.05 1.4728 3.5519
age_group*sample_typ B   3 2.8993 0.5239 30 5.53 <.0001 0.05 1.8294 3.9692
age_group*sample_typ C   3 3.3589 0.6312 30 5.32 <.0001 0.05 2.0698 4.6479
hospbi*age_gr*sample A 3 1 1.6201 1.4067 30 1.15 0.2585 0.05 -1.2527 4.4929
hospbi*age_gr*sample B 3 1 1.7887 1.4477 30 1.24 0.2262 0.05 -1.1680 4.7454
hospbi*age_gr*sample C 3 1 1.7493 1.7442 30 1.00 0.3239 0.05 -1.8129 5.3115
hospbi*age_gr*sample A 3 2 3.2800 1.7228 30 1.90 0.0666 0.05 -0.2385 6.7984
hospbi*age_gr*sample B 3 2 5.2279 1.7731 30 2.95 0.0061 0.05 1.6067 8.8491
hospbi*age_gr*sample C 3 2 5.0100 2.1362 30 2.35 0.0258 0.05 0.6472 9.3727
hospbi*age_gr*sample A 3 3 1.4517 0.8614 30 1.69 0.1023 0.05 -0.3075 3.2110
hospbi*age_gr*sample B 3 3 1.4407 0.8866 30 1.63 0.1146 0.05 -0.3699 3.2513
hospbi*age_gr*sample C 3 3 1.6994 1.0681 30 1.59 0.1221 0.05 -0.4820 3.8808
hospbi*age_gr*sample A 6 1 2.6619 1.2182 30 2.19 0.0368 0.05 0.1740 5.1499
hospbi*age_gr*sample B 6 1 3.3675 1.2538 30 2.69 0.0117 0.05 0.8069 5.9280
hospbi*age_gr*sample C 6 1 2.9062 1.5105 30 1.92 0.0639 0.05 -0.1787 5.9912
hospbi*age_gr*sample A 6 2 1.1018 1.7228 30 0.64 0.5273 0.05 -2.4166 4.6203
hospbi*age_gr*sample B 6 2 1.0034 1.7731 30 0.57 0.5757 0.05 -2.6177 4.6246
hospbi*age_gr*sample C 6 2 1.3581 2.1362 30 0.64 0.5298 0.05 -3.0047 5.7208
hospbi*age_gr*sample A 6 3 2.5845 0.9209 30 2.81 0.0087 0.05 0.7038 4.4652
hospbi*age_gr*sample B 6 3 3.3927 0.9478 30 3.58 0.0012 0.05 1.4571 5.3282
hospbi*age_gr*sample C 6 3 2.9867 1.1419 30 2.62 0.0138 0.05 0.6547 5.3187
hospbi*age_gr*sample A 9 1 5.1326 1.2182 30 4.21 0.0002 0.05 2.6447 7.6205
hospbi*age_gr*sample B 9 1 4.0906 1.2538 30 3.26 0.0028 0.05 1.5301 6.6512
hospbi*age_gr*sample C 9 1 4.9769 1.5105 30 3.29 0.0025 0.05 1.8919 8.0618
hospbi*age_gr*sample A 9 2 1.6793 2.4364 30 0.69 0.4960 0.05 -3.2966 6.6551
hospbi*age_gr*sample B 9 2 1.6145 2.5075 30 0.64 0.5246 0.05 -3.5065 6.7356
hospbi*age_gr*sample C 9 2 1.0539 3.0211 30 0.35 0.7296 0.05 -5.1160 7.2238
hospbi*age_gr*sample A 9 3 3.5008 0.8614 30 4.06 0.0003 0.05 1.7416 5.2601
hospbi*age_gr*sample B 9 3 3.8646 0.8866 30 4.36 0.0001 0.05 2.0540 5.6752
hospbi*age_gr*sample C 9 3 5.3905 1.0681 30 5.05 <.0001 0.05 3.2091 7.5718
Differences of Least Squares Means
Effect sample_type2 hospbin age_group _sample_type2 hospbin _age_group Estimate Standard
Error
DF t Value Pr > |t| Adjustment Adj P Alpha Lower Upper Adj Lower Adj Upper
hospbin   3     6   0.2117 1.1562 30 0.18 0.8560 Tukey-Kramer 0.9817 0.05 -2.1497 2.5730 -2.6388 3.0621
hospbin   3     9   -0.8929 1.2981 30 -0.69 0.4968 Tukey-Kramer 0.7723 0.05 -3.5440 1.7582 -4.0930 2.3073
hospbin   6     9   -1.1045 1.2798 30 -0.86 0.3949 Tukey-Kramer 0.6673 0.05 -3.7182 1.5091 -4.2595 2.0504
age_group     1     2 0.7739 1.4304 30 0.54 0.5925 Tukey-Kramer 0.8518 0.05 -2.1475 3.6952 -2.7525 4.3003
age_group     1     3 0.2203 0.9410 30 0.23 0.8165 Tukey-Kramer 0.9703 0.05 -1.7016 2.1421 -2.0996 2.5401
age_group     2     3 -0.5536 1.3146 30 -0.42 0.6766 Tukey-Kramer 0.9072 0.05 -3.2383 2.1311 -3.7944 2.6871
hospbin*age_group   3 1   3 2 -2.7866 2.3273 30 -1.20 0.2406 Tukey-Kramer 0.9509 0.05 -7.5396 1.9664 -10.5540 4.9808
hospbin*age_group   3 1   3 3 0.1888 1.7260 30 0.11 0.9136 Tukey-Kramer 1.0000 0.05 -3.3361 3.7137 -5.5717 5.9492
hospbin*age_group   3 1   6 1 -1.2592 1.9472 30 -0.65 0.5228 Tukey-Kramer 0.9991 0.05 -5.2358 2.7175 -7.7578 5.2395
hospbin*age_group   3 1   6 2 0.5649 2.3273 30 0.24 0.8099 Tukey-Kramer 1.0000 0.05 -4.1881 5.3179 -7.2024 8.3323
hospbin*age_group   3 1   6 3 -1.2686 1.7593 30 -0.72 0.4764 Tukey-Kramer 0.9981 0.05 -4.8615 2.3243 -7.1402 4.6030
hospbin*age_group   3 1   9 1 -3.0140 1.9472 30 -1.55 0.1321 Tukey-Kramer 0.8240 0.05 -6.9906 0.9627 -9.5126 3.4847
hospbin*age_group   3 1   9 2 0.2701 2.9438 30 0.09 0.9275 Tukey-Kramer 1.0000 0.05 -5.7420 6.2822 -9.5549 10.0952
hospbin*age_group   3 1   9 3 -2.5326 1.7260 30 -1.47 0.1527 Tukey-Kramer 0.8614 0.05 -6.0575 0.9923 -8.2930 3.2279
hospbin*age_group   3 2   3 3 2.9753 2.0155 30 1.48 0.1503 Tukey-Kramer 0.8575 0.05 -1.1409 7.0916 -3.7514 9.7021
hospbin*age_group   3 2   6 1 1.5274 2.2079 30 0.69 0.4944 Tukey-Kramer 0.9985 0.05 -2.9817 6.0365 -5.8414 8.8962
hospbin*age_group   3 2   6 2 3.3515 2.5494 30 1.31 0.1986 Tukey-Kramer 0.9190 0.05 -1.8551 8.5582 -5.1572 11.8603
hospbin*age_group   3 2   6 3 1.5180 2.0441 30 0.74 0.4635 Tukey-Kramer 0.9976 0.05 -2.6566 5.6926 -5.3042 8.3402
hospbin*age_group   3 2   9 1 -0.2274 2.2079 30 -0.10 0.9186 Tukey-Kramer 1.0000 0.05 -4.7365 4.2817 -7.5962 7.1414
hospbin*age_group   3 2   9 2 3.0567 3.1224 30 0.98 0.3354 Tukey-Kramer 0.9851 0.05 -3.3201 9.4335 -7.3643 13.4777
hospbin*age_group   3 2   9 3 0.2540 2.0155 30 0.13 0.9006 Tukey-Kramer 1.0000 0.05 -3.8622 4.3702 -6.4728 6.9807
hospbin*age_group   3 3   6 1 -1.4479 1.5612 30 -0.93 0.3611 Tukey-Kramer 0.9894 0.05 -4.6363 1.7405 -6.6585 3.7626
hospbin*age_group   3 3   6 2 0.3762 2.0155 30 0.19 0.8532 Tukey-Kramer 1.0000 0.05 -3.7400 4.4924 -6.3506 7.1029
hospbin*age_group   3 3   6 3 -1.4574 1.3195 30 -1.10 0.2782 Tukey-Kramer 0.9690 0.05 -4.1520 1.2373 -5.8610 2.9463
hospbin*age_group   3 3   9 1 -3.2028 1.5612 30 -2.05 0.0490 Tukey-Kramer 0.5223 0.05 -6.3912 -0.01436 -8.4133 2.0078
hospbin*age_group   3 3   9 2 0.08136 2.7041 30 0.03 0.9762 Tukey-Kramer 1.0000 0.05 -5.4411 5.6038 -8.9435 9.1062
hospbin*age_group   3 3   9 3 -2.7214 1.2747 30 -2.13 0.0411 Tukey-Kramer 0.4703 0.05 -5.3247 -0.1180 -6.9757 1.5330
hospbin*age_group   6 1   6 2 1.8241 2.2079 30 0.83 0.4152 Tukey-Kramer 0.9950 0.05 -2.6850 6.3332 -5.5447 9.1929
hospbin*age_group   6 1   6 3 -0.00941 1.5979 30 -0.01 0.9953 Tukey-Kramer 1.0000 0.05 -3.2728 3.2540 -5.3425 5.3237
hospbin*age_group   6 1   9 1 -1.7548 1.8027 30 -0.97 0.3381 Tukey-Kramer 0.9856 0.05 -5.4365 1.9268 -7.7714 4.2618
hospbin*age_group   6 1   9 2 1.5293 2.8504 30 0.54 0.5955 Tukey-Kramer 0.9998 0.05 -4.2919 7.3505 -7.9838 11.0424
hospbin*age_group   6 1   9 3 -1.2734 1.5612 30 -0.82 0.4211 Tukey-Kramer 0.9955 0.05 -4.4618 1.9150 -6.4839 3.9371
hospbin*age_group   6 2   6 3 -1.8335 2.0441 30 -0.90 0.3769 Tukey-Kramer 0.9915 0.05 -6.0081 2.3411 -8.6557 4.9887
hospbin*age_group   6 2   9 1 -3.5789 2.2079 30 -1.62 0.1155 Tukey-Kramer 0.7862 0.05 -8.0880 0.9302 -10.9477 3.7899
hospbin*age_group   6 2   9 2 -0.2948 3.1224 30 -0.09 0.9254 Tukey-Kramer 1.0000 0.05 -6.6716 6.0820 -10.7158 10.1262
hospbin*age_group   6 2   9 3 -3.0975 2.0155 30 -1.54 0.1348 Tukey-Kramer 0.8294 0.05 -7.2137 1.0187 -9.8243 3.6292
hospbin*age_group   6 3   9 1 -1.7454 1.5979 30 -1.09 0.2834 Tukey-Kramer 0.9710 0.05 -5.0088 1.5180 -7.0785 3.5877
hospbin*age_group   6 3   9 2 1.5387 2.7255 30 0.56 0.5766 Tukey-Kramer 0.9997 0.05 -4.0274 7.1048 -7.5575 10.6349
hospbin*age_group   6 3   9 3 -1.2640 1.3195 30 -0.96 0.3457 Tukey-Kramer 0.9870 0.05 -3.9587 1.4307 -5.6677 3.1397
hospbin*age_group   9 1   9 2 3.2841 2.8504 30 1.15 0.2583 Tukey-Kramer 0.9604 0.05 -2.5371 9.1053 -6.2289 12.7972
hospbin*age_group   9 1   9 3 0.4814 1.5612 30 0.31 0.7599 Tukey-Kramer 1.0000 0.05 -2.7070 3.6698 -4.7291 5.6919
hospbin*age_group   9 2   9 3 -2.8027 2.7041 30 -1.04 0.3083 Tukey-Kramer 0.9788 0.05 -8.3252 2.7198 -11.8276 6.2222
sample_type2 A     B     -0.3086 0.2595 30 -1.19 0.2436 Tukey-Kramer 0.4686 0.05 -0.8386 0.2213 -0.9484 0.3311
sample_type2 A     C     -0.4576 0.2580 30 -1.77 0.0863 Tukey-Kramer 0.1957 0.05 -0.9845 0.06942 -1.0937 0.1786
sample_type2 B     C     -0.1489 0.2956 30 -0.50 0.6181 Tukey-Kramer 0.8700 0.05 -0.7526 0.4547 -0.8776 0.5798
hospbin*sample_type2 A 3   B 3   -0.7018 0.4243 30 -1.65 0.1086 Tukey-Kramer 0.7680 0.05 -1.5684 0.1648 -2.1179 0.7143
hospbin*sample_type2 A 3   C 3   -0.7023 0.4219 30 -1.66 0.1064 Tukey-Kramer 0.7621 0.05 -1.5639 0.1594 -2.1104 0.7058
hospbin*sample_type2 A 3   A 6   0.001204 1.1050 30 0.00 0.9991 Tukey-Kramer 1.0000 0.05 -2.2555 2.2579 -3.6867 3.6891
hospbin*sample_type2 A 3   B 6   -0.4706 1.1207 30 -0.42 0.6775 Tukey-Kramer 1.0000 0.05 -2.7593 1.8181 -4.2108 3.2696
hospbin*sample_type2 A 3   C 6   -0.2997 1.2400 30 -0.24 0.8106 Tukey-Kramer 1.0000 0.05 -2.8321 2.2327 -4.4381 3.8387
hospbin*sample_type2 A 3   A 9   -1.3203 1.2406 30 -1.06 0.2957 Tukey-Kramer 0.9751 0.05 -3.8539 1.2133 -5.4607 2.8201
hospbin*sample_type2 A 3   B 9   -1.0726 1.2620 30 -0.85 0.4021 Tukey-Kramer 0.9940 0.05 -3.6500 1.5048 -5.2847 3.1394
hospbin*sample_type2 A 3   C 9   -1.6898 1.4235 30 -1.19 0.2445 Tukey-Kramer 0.9532 0.05 -4.5971 1.2175 -6.4409 3.0613
hospbin*sample_type2 B 3   C 3   -0.00046 0.4833 30 -0.00 0.9992 Tukey-Kramer 1.0000 0.05 -0.9875 0.9865 -1.6134 1.6125
hospbin*sample_type2 B 3   A 6   0.7030 1.1218 30 0.63 0.5356 Tukey-Kramer 0.9993 0.05 -1.5880 2.9940 -3.0410 4.4470
hospbin*sample_type2 B 3   B 6   0.2312 1.1372 30 0.20 0.8403 Tukey-Kramer 1.0000 0.05 -2.0913 2.5538 -3.5643 4.0268
hospbin*sample_type2 B 3   C 6   0.4021 1.2550 30 0.32 0.7509 Tukey-Kramer 1.0000 0.05 -2.1609 2.9651 -3.7864 4.5906
hospbin*sample_type2 B 3   A 9   -0.6185 1.2556 30 -0.49 0.6259 Tukey-Kramer 0.9999 0.05 -3.1827 1.9457 -4.8089 3.5720
hospbin*sample_type2 B 3   B 9   -0.3708 1.2768 30 -0.29 0.7735 Tukey-Kramer 1.0000 0.05 -2.9784 2.2367 -4.6321 3.8904
hospbin*sample_type2 B 3   C 9   -0.9880 1.4366 30 -0.69 0.4969 Tukey-Kramer 0.9986 0.05 -3.9220 1.9460 -5.7828 3.8068
hospbin*sample_type2 C 3   A 6   0.7035 1.2493 30 0.56 0.5776 Tukey-Kramer 0.9997 0.05 -1.8479 3.2549 -3.4661 4.8730
hospbin*sample_type2 C 3   B 6   0.2317 1.2632 30 0.18 0.8557 Tukey-Kramer 1.0000 0.05 -2.3481 2.8115 -3.9842 4.4476
hospbin*sample_type2 C 3   C 6   0.4026 1.3701 30 0.29 0.7709 Tukey-Kramer 1.0000 0.05 -2.3957 3.2008 -4.1703 4.9754
hospbin*sample_type2 C 3   A 9   -0.6180 1.3707 30 -0.45 0.6553 Tukey-Kramer 0.9999 0.05 -3.4173 2.1813 -5.1927 3.9566
hospbin*sample_type2 C 3   B 9   -0.3704 1.3901 30 -0.27 0.7917 Tukey-Kramer 1.0000 0.05 -3.2094 2.4687 -5.0099 4.2692
hospbin*sample_type2 C 3   C 9   -0.9875 1.5383 30 -0.64 0.5258 Tukey-Kramer 0.9991 0.05 -4.1291 2.1540 -6.1215 4.1464
hospbin*sample_type2 A 6   B 6   -0.4718 0.4096 30 -1.15 0.2585 Tukey-Kramer 0.9605 0.05 -1.3082 0.3647 -1.8387 0.8951
hospbin*sample_type2 A 6   C 6   -0.3009 0.4072 30 -0.74 0.4657 Tukey-Kramer 0.9977 0.05 -1.1326 0.5308 -1.6601 1.0582
hospbin*sample_type2 A 6   A 9   -1.3215 1.2230 30 -1.08 0.2885 Tukey-Kramer 0.9728 0.05 -3.8193 1.1763 -5.4034 2.7604
hospbin*sample_type2 A 6   B 9   -1.0738 1.2448 30 -0.86 0.3952 Tukey-Kramer 0.9934 0.05 -3.6161 1.4684 -5.2284 3.0807
hospbin*sample_type2 A 6   C 9   -1.6910 1.4083 30 -1.20 0.2392 Tukey-Kramer 0.9501 0.05 -4.5671 1.1851 -6.3912 3.0092
hospbin*sample_type2 B 6   C 6   0.1709 0.4665 30 0.37 0.7167 Tukey-Kramer 1.0000 0.05 -0.7818 1.1235 -1.3860 1.7278
hospbin*sample_type2 B 6   A 9   -0.8497 1.2372 30 -0.69 0.4975 Tukey-Kramer 0.9986 0.05 -3.3765 1.6770 -4.9789 3.2795
hospbin*sample_type2 B 6   B 9   -0.6021 1.2587 30 -0.48 0.6359 Tukey-Kramer 0.9999 0.05 -3.1727 1.9686 -4.8031 3.5990
hospbin*sample_type2 B 6   C 9   -1.2192 1.4206 30 -0.86 0.3976 Tukey-Kramer 0.9936 0.05 -4.1205 1.6821 -5.9606 3.5221
hospbin*sample_type2 C 6   A 9   -1.0206 1.3462 30 -0.76 0.4543 Tukey-Kramer 0.9972 0.05 -3.7700 1.7288 -5.5137 3.4725
hospbin*sample_type2 C 6   B 9   -0.7729 1.3660 30 -0.57 0.5757 Tukey-Kramer 0.9997 0.05 -3.5628 2.0169 -5.3321 3.7863
hospbin*sample_type2 C 6   C 9   -1.3901 1.5165 30 -0.92 0.3667 Tukey-Kramer 0.9902 0.05 -4.4872 1.7071 -6.4515 3.6713
hospbin*sample_type2 A 9   B 9   0.2477 0.5083 30 0.49 0.6296 Tukey-Kramer 0.9999 0.05 -0.7903 1.2856 -1.4486 1.9439
hospbin*sample_type2 A 9   C 9   -0.3695 0.5054 30 -0.73 0.4704 Tukey-Kramer 0.9979 0.05 -1.4016 0.6626 -2.0562 1.3172
hospbin*sample_type2 B 9   C 9   -0.6172 0.5789 30 -1.07 0.2949 Tukey-Kramer 0.9749 0.05 -1.7994 0.5651 -2.5492 1.3149
age_group*sample_typ A   1 B   1 0.05596 0.3957 30 0.14 0.8885 Tukey-Kramer 1.0000 0.05 -0.7521 0.8640 -1.2646 1.3765
age_group*sample_typ A   1 C   1 -0.07256 0.3934 30 -0.18 0.8549 Tukey-Kramer 1.0000 0.05 -0.8761 0.7309 -1.3856 1.2405
age_group*sample_typ A   1 A   2 1.1179 1.3670 30 0.82 0.4200 Tukey-Kramer 0.9954 0.05 -1.6740 3.9097 -3.4446 5.6804
age_group*sample_typ A   1 B   2 0.5229 1.3953 30 0.37 0.7105 Tukey-Kramer 1.0000 0.05 -2.3267 3.3726 -4.1340 5.1798
age_group*sample_typ A   1 C   2 0.6642 1.6056 30 0.41 0.6820 Tukey-Kramer 1.0000 0.05 -2.6148 3.9433 -4.6943 6.0228
age_group*sample_typ A   1 A   3 0.6259 0.8993 30 0.70 0.4918 Tukey-Kramer 0.9985 0.05 -1.2108 2.4625 -2.3756 3.6273
age_group*sample_typ A   1 B   3 0.2389 0.9078 30 0.26 0.7942 Tukey-Kramer 1.0000 0.05 -1.6151 2.0929 -2.7909 3.2687
age_group*sample_typ A   1 C   3 -0.2206 0.9737 30 -0.23 0.8223 Tukey-Kramer 1.0000 0.05 -2.2091 1.7679 -3.4703 3.0290
age_group*sample_typ B   1 C   1 -0.1285 0.4507 30 -0.29 0.7775 Tukey-Kramer 1.0000 0.05 -1.0489 0.7919 -1.6326 1.3756
age_group*sample_typ B   1 A   2 1.0619 1.3789 30 0.77 0.4473 Tukey-Kramer 0.9969 0.05 -1.7542 3.8780 -3.5402 5.6640
age_group*sample_typ B   1 B   2 0.4670 1.4069 30 0.33 0.7423 Tukey-Kramer 1.0000 0.05 -2.4064 3.3403 -4.2287 5.1626
age_group*sample_typ B   1 C   2 0.6083 1.6157 30 0.38 0.7092 Tukey-Kramer 1.0000 0.05 -2.6914 3.9079 -4.7840 6.0006
age_group*sample_typ B   1 A   3 0.5699 0.9172 30 0.62 0.5391 Tukey-Kramer 0.9993 0.05 -1.3033 2.4432 -2.4914 3.6312
age_group*sample_typ B   1 B   3 0.1830 0.9256 30 0.20 0.8446 Tukey-Kramer 1.0000 0.05 -1.7073 2.0732 -2.9061 3.2720
age_group*sample_typ B   1 C   3 -0.2766 0.9903 30 -0.28 0.7819 Tukey-Kramer 1.0000 0.05 -2.2990 1.7458 -3.5816 3.0284
age_group*sample_typ C   1 A   2 1.1904 1.4711 30 0.81 0.4248 Tukey-Kramer 0.9957 0.05 -1.8140 4.1949 -3.7195 6.1003
age_group*sample_typ C   1 B   2 0.5955 1.4975 30 0.40 0.6937 Tukey-Kramer 1.0000 0.05 -2.4627 3.6537 -4.4023 5.5933
age_group*sample_typ C   1 C   2 0.7368 1.6951 30 0.43 0.6669 Tukey-Kramer 1.0000 0.05 -2.7250 4.1986 -4.9205 6.3941
age_group*sample_typ C   1 A   3 0.6984 1.0508 30 0.66 0.5113 Tukey-Kramer 0.9989 0.05 -1.4476 2.8445 -2.8086 4.2055
age_group*sample_typ C   1 B   3 0.3115 1.0581 30 0.29 0.7705 Tukey-Kramer 1.0000 0.05 -1.8494 2.4724 -3.2199 3.8429
age_group*sample_typ C   1 C   3 -0.1481 1.1151 30 -0.13 0.8953 Tukey-Kramer 1.0000 0.05 -2.4254 2.1293 -3.8698 3.5736
age_group*sample_typ A   2 B   2 -0.5949 0.6130 30 -0.97 0.3395 Tukey-Kramer 0.9859 0.05 -1.8468 0.6569 -2.6407 1.4509
age_group*sample_typ A   2 C   2 -0.4536 0.6095 30 -0.74 0.4625 Tukey-Kramer 0.9976 0.05 -1.6984 0.7911 -2.4878 1.5806
age_group*sample_typ A   2 A   3 -0.4920 1.2563 30 -0.39 0.6981 Tukey-Kramer 1.0000 0.05 -3.0577 2.0737 -4.6849 3.7009
age_group*sample_typ A   2 B   3 -0.8789 1.2624 30 -0.70 0.4916 Tukey-Kramer 0.9985 0.05 -3.4571 1.6992 -5.0922 3.3343
age_group*sample_typ A   2 C   3 -1.3385 1.3106 30 -1.02 0.3153 Tukey-Kramer 0.9806 0.05 -4.0150 1.3380 -5.7125 3.0355
age_group*sample_typ B   2 C   2 0.1413 0.6982 30 0.20 0.8410 Tukey-Kramer 1.0000 0.05 -1.2845 1.5672 -2.1888 2.4715
age_group*sample_typ B   2 A   3 0.1029 1.2870 30 0.08 0.9368 Tukey-Kramer 1.0000 0.05 -2.5255 2.7314 -4.1925 4.3983
age_group*sample_typ B   2 B   3 -0.2840 1.2930 30 -0.22 0.8276 Tukey-Kramer 1.0000 0.05 -2.9246 2.3566 -4.5993 4.0312
age_group*sample_typ B   2 C   3 -0.7436 1.3400 30 -0.55 0.5831 Tukey-Kramer 0.9997 0.05 -3.4803 1.9931 -5.2159 3.7288
age_group*sample_typ C   2 A   3 -0.03837 1.5124 30 -0.03 0.9799 Tukey-Kramer 1.0000 0.05 -3.1271 3.0503 -5.0860 5.0092
age_group*sample_typ C   2 B   3 -0.4253 1.5175 30 -0.28 0.7812 Tukey-Kramer 1.0000 0.05 -3.5244 2.6737 -5.4898 4.6392
age_group*sample_typ C   2 C   3 -0.8849 1.5578 30 -0.57 0.5742 Tukey-Kramer 0.9997 0.05 -4.0662 2.2965 -6.0839 4.3141
age_group*sample_typ A   3 B   3 -0.3870 0.2717 30 -1.42 0.1647 Tukey-Kramer 0.8795 0.05 -0.9418 0.1679 -1.2937 0.5198
age_group*sample_typ A   3 C   3 -0.8465 0.2701 30 -3.13 0.0038 Tukey-Kramer 0.0789 0.05 -1.3982 -0.2948 -1.7481 0.05507
age_group*sample_typ B   3 C   3 -0.4595 0.3094 30 -1.49 0.1479 Tukey-Kramer 0.8536 0.05 -1.0915 0.1724 -1.4923 0.5732
hospbi*age_gr*sample A 3 1 B 3 1 -0.1686 0.7507 30 -0.22 0.8239 Tukey-Kramer 1.0000 0.05 -1.7018 1.3647 -3.2165 2.8794
hospbi*age_gr*sample A 3 1 C 3 1 -0.1292 0.7465 30 -0.17 0.8638 Tukey-Kramer 1.0000 0.05 -1.6537 1.3954 -3.1598 2.9015
hospbi*age_gr*sample A 3 1 A 3 2 -1.6599 2.2241 30 -0.75 0.4613 Tukey-Kramer 1.0000 0.05 -6.2022 2.8825 -10.6898 7.3700
hospbi*age_gr*sample A 3 1 B 3 2 -3.6078 2.2633 30 -1.59 0.1214 Tukey-Kramer 0.9953 0.05 -8.2301 1.0146 -12.7967 5.5812
hospbi*age_gr*sample A 3 1 C 3 2 -3.3898 2.5578 30 -1.33 0.1951 Tukey-Kramer 0.9997 0.05 -8.6135 1.8338 -13.7742 6.9946
hospbi*age_gr*sample A 3 1 A 3 3 0.1684 1.6495 30 0.10 0.9194 Tukey-Kramer 1.0000 0.05 -3.2002 3.5371 -6.5283 6.8652
hospbi*age_gr*sample A 3 1 B 3 3 0.1795 1.6627 30 0.11 0.9148 Tukey-Kramer 1.0000 0.05 -3.2163 3.5752 -6.5712 6.9301
hospbi*age_gr*sample A 3 1 C 3 3 -0.07926 1.7662 30 -0.04 0.9645 Tukey-Kramer 1.0000 0.05 -3.6864 3.5279 -7.2501 7.0916
hospbi*age_gr*sample A 3 1 A 6 1 -1.0418 1.8609 30 -0.56 0.5797 Tukey-Kramer 1.0000 0.05 -4.8422 2.7586 -8.5968 6.5132
hospbi*age_gr*sample A 3 1 B 6 1 -1.7473 1.8843 30 -0.93 0.3612 Tukey-Kramer 1.0000 0.05 -5.5956 2.1010 -9.3976 5.9029
hospbi*age_gr*sample A 3 1 C 6 1 -1.2861 2.0641 30 -0.62 0.5379 Tukey-Kramer 1.0000 0.05 -5.5015 2.9293 -9.6662 7.0940
hospbi*age_gr*sample A 3 1 A 6 2 0.5183 2.2241 30 0.23 0.8173 Tukey-Kramer 1.0000 0.05 -4.0240 5.0606 -8.5116 9.5482
hospbi*age_gr*sample A 3 1 B 6 2 0.6167 2.2633 30 0.27 0.7871 Tukey-Kramer 1.0000 0.05 -4.0056 5.2390 -8.5723 9.8057
hospbi*age_gr*sample A 3 1 C 6 2 0.2621 2.5578 30 0.10 0.9191 Tukey-Kramer 1.0000 0.05 -4.9616 5.4857 -10.1224 10.6465
hospbi*age_gr*sample A 3 1 A 6 3 -0.9644 1.6813 30 -0.57 0.5705 Tukey-Kramer 1.0000 0.05 -4.3980 2.4693 -7.7903 5.8616
hospbi*age_gr*sample A 3 1 B 6 3 -1.7725 1.6962 30 -1.05 0.3044 Tukey-Kramer 1.0000 0.05 -5.2365 1.6915 -8.6589 5.1138
hospbi*age_gr*sample A 3 1 C 6 3 -1.3666 1.8118 30 -0.75 0.4566 Tukey-Kramer 1.0000 0.05 -5.0667 2.3336 -8.7223 5.9892
hospbi*age_gr*sample A 3 1 A 9 1 -3.5125 1.8609 30 -1.89 0.0688 Tukey-Kramer 0.9673 0.05 -7.3128 0.2879 -11.0674 4.0425
hospbi*age_gr*sample A 3 1 B 9 1 -2.4705 1.8843 30 -1.31 0.1998 Tukey-Kramer 0.9997 0.05 -6.3188 1.3778 -10.1207 5.1798
hospbi*age_gr*sample A 3 1 C 9 1 -3.3567 2.0641 30 -1.63 0.1144 Tukey-Kramer 0.9939 0.05 -7.5721 0.8587 -11.7368 5.0234
hospbi*age_gr*sample A 3 1 A 9 2 -0.05915 2.8133 30 -0.02 0.9834 Tukey-Kramer 1.0000 0.05 -5.8048 5.6865 -11.4812 11.3629
hospbi*age_gr*sample A 3 1 B 9 2 0.005601 2.8752 30 0.00 0.9985 Tukey-Kramer 1.0000 0.05 -5.8662 5.8774 -11.6674 11.6786
hospbi*age_gr*sample A 3 1 C 9 2 0.5662 3.3325 30 0.17 0.8662 Tukey-Kramer 1.0000 0.05 -6.2397 7.3721 -12.9636 14.0961
hospbi*age_gr*sample A 3 1 A 9 3 -1.8807 1.6495 30 -1.14 0.2632 Tukey-Kramer 1.0000 0.05 -5.2494 1.4880 -8.5775 4.8161
hospbi*age_gr*sample A 3 1 B 9 3 -2.2444 1.6627 30 -1.35 0.1872 Tukey-Kramer 0.9995 0.05 -5.6402 1.1513 -8.9951 4.5062
hospbi*age_gr*sample A 3 1 C 9 3 -3.7703 1.7662 30 -2.13 0.0411 Tukey-Kramer 0.9009 0.05 -7.3775 -0.1632 -10.9411 3.4005
hospbi*age_gr*sample B 3 1 C 3 1 0.03939 0.8551 30 0.05 0.9636 Tukey-Kramer 1.0000 0.05 -1.7069 1.7857 -3.4322 3.5110
hospbi*age_gr*sample B 3 1 A 3 2 -1.4913 2.2503 30 -0.66 0.5126 Tukey-Kramer 1.0000 0.05 -6.0871 3.1045 -10.6275 7.6449
hospbi*age_gr*sample B 3 1 B 3 2 -3.4392 2.2891 30 -1.50 0.1434 Tukey-Kramer 0.9978 0.05 -8.1141 1.2357 -12.7327 5.8543
hospbi*age_gr*sample B 3 1 C 3 2 -3.2213 2.5806 30 -1.25 0.2216 Tukey-Kramer 0.9999 0.05 -8.4915 2.0490 -13.6983 7.2557
hospbi*age_gr*sample B 3 1 A 3 3 0.3370 1.6846 30 0.20 0.8428 Tukey-Kramer 1.0000 0.05 -3.1035 3.7774 -6.5025 7.1764
hospbi*age_gr*sample B 3 1 B 3 3 0.3480 1.6976 30 0.20 0.8390 Tukey-Kramer 1.0000 0.05 -3.1190 3.8150 -6.5442 7.2402
hospbi*age_gr*sample B 3 1 C 3 3 0.08929 1.7991 30 0.05 0.9607 Tukey-Kramer 1.0000 0.05 -3.5850 3.7636 -7.2150 7.3936
hospbi*age_gr*sample B 3 1 A 6 1 -0.8732 1.8921 30 -0.46 0.6477 Tukey-Kramer 1.0000 0.05 -4.7374 2.9909 -8.5550 6.8085
hospbi*age_gr*sample B 3 1 B 6 1 -1.5788 1.9152 30 -0.82 0.4162 Tukey-Kramer 1.0000 0.05 -5.4901 2.3325 -9.3543 6.1967
hospbi*age_gr*sample B 3 1 C 6 1 -1.1175 2.0923 30 -0.53 0.5972 Tukey-Kramer 1.0000 0.05 -5.3906 3.1555 -9.6121 7.3770
hospbi*age_gr*sample B 3 1 A 6 2 0.6869 2.2503 30 0.31 0.7623 Tukey-Kramer 1.0000 0.05 -3.9089 5.2827 -8.4494 9.8231
hospbi*age_gr*sample B 3 1 B 6 2 0.7853 2.2891 30 0.34 0.7340 Tukey-Kramer 1.0000 0.05 -3.8896 5.4601 -8.5082 10.0787
hospbi*age_gr*sample B 3 1 C 6 2 0.4306 2.5806 30 0.17 0.8686 Tukey-Kramer 1.0000 0.05 -4.8396 5.7009 -10.0464 10.9076
hospbi*age_gr*sample B 3 1 A 6 3 -0.7958 1.7158 30 -0.46 0.6461 Tukey-Kramer 1.0000 0.05 -4.2999 2.7083 -7.7618 6.1702
hospbi*age_gr*sample B 3 1 B 6 3 -1.6040 1.7304 30 -0.93 0.3614 Tukey-Kramer 1.0000 0.05 -5.1379 1.9299 -8.6292 5.4212
hospbi*age_gr*sample B 3 1 C 6 3 -1.1980 1.8438 30 -0.65 0.5208 Tukey-Kramer 1.0000 0.05 -4.9637 2.5676 -8.6839 6.2879
hospbi*age_gr*sample B 3 1 A 9 1 -3.3439 1.8921 30 -1.77 0.0873 Tukey-Kramer 0.9837 0.05 -7.2081 0.5202 -11.0257 4.3378
hospbi*age_gr*sample B 3 1 B 9 1 -2.3019 1.9152 30 -1.20 0.2388 Tukey-Kramer 0.9999 0.05 -6.2132 1.6094 -10.0774 5.4735
hospbi*age_gr*sample B 3 1 C 9 1 -3.1882 2.0923 30 -1.52 0.1380 Tukey-Kramer 0.9974 0.05 -7.4612 1.0849 -11.6827 5.3064
hospbi*age_gr*sample B 3 1 A 9 2 0.1094 2.8341 30 0.04 0.9695 Tukey-Kramer 1.0000 0.05 -5.6786 5.8974 -11.3969 11.6157
hospbi*age_gr*sample B 3 1 B 9 2 0.1742 2.8955 30 0.06 0.9524 Tukey-Kramer 1.0000 0.05 -5.7392 6.0875 -11.5813 11.9296
hospbi*age_gr*sample B 3 1 C 9 2 0.7348 3.3501 30 0.22 0.8279 Tukey-Kramer 1.0000 0.05 -6.1069 7.5765 -12.8663 14.3358
hospbi*age_gr*sample B 3 1 A 9 3 -1.7121 1.6846 30 -1.02 0.3176 Tukey-Kramer 1.0000 0.05 -5.1526 1.7283 -8.5516 5.1273
hospbi*age_gr*sample B 3 1 B 9 3 -2.0759 1.6976 30 -1.22 0.2309 Tukey-Kramer 0.9999 0.05 -5.5429 1.3911 -8.9681 4.8163
hospbi*age_gr*sample B 3 1 C 9 3 -3.6018 1.7991 30 -2.00 0.0544 Tukey-Kramer 0.9427 0.05 -7.2760 0.07250 -10.9061 3.7025
hospbi*age_gr*sample C 3 1 A 3 2 -1.5307 2.4516 30 -0.62 0.5371 Tukey-Kramer 1.0000 0.05 -6.5375 3.4762 -11.4841 8.4227
hospbi*age_gr*sample C 3 1 B 3 2 -3.4786 2.4872 30 -1.40 0.1722 Tukey-Kramer 0.9992 0.05 -8.5582 1.6010 -13.5765 6.6193
hospbi*age_gr*sample C 3 1 C 3 2 -3.2607 2.7579 30 -1.18 0.2464 Tukey-Kramer 0.9999 0.05 -8.8930 2.3716 -14.4574 7.9361
hospbi*age_gr*sample C 3 1 A 3 3 0.2976 1.9453 30 0.15 0.8794 Tukey-Kramer 1.0000 0.05 -3.6753 4.2705 -7.6004 8.1955
hospbi*age_gr*sample C 3 1 B 3 3 0.3086 1.9566 30 0.16 0.8757 Tukey-Kramer 1.0000 0.05 -3.6873 4.3045 -7.6351 8.2523
hospbi*age_gr*sample C 3 1 C 3 3 0.04990 2.0453 30 0.02 0.9807 Tukey-Kramer 1.0000 0.05 -4.1271 4.2269 -8.2538 8.3536
hospbi*age_gr*sample C 3 1 A 6 1 -0.9126 2.1275 30 -0.43 0.6710 Tukey-Kramer 1.0000 0.05 -5.2576 3.4323 -9.5503 7.7250
hospbi*age_gr*sample C 3 1 B 6 1 -1.6182 2.1481 30 -0.75 0.4571 Tukey-Kramer 1.0000 0.05 -6.0051 2.7688 -10.3393 7.1029
hospbi*age_gr*sample C 3 1 C 6 1 -1.1569 2.3074 30 -0.50 0.6198 Tukey-Kramer 1.0000 0.05 -5.8692 3.5554 -10.5248 8.2110
hospbi*age_gr*sample C 3 1 A 6 2 0.6475 2.4516 30 0.26 0.7935 Tukey-Kramer 1.0000 0.05 -4.3594 5.6544 -9.3059 10.6009
hospbi*age_gr*sample C 3 1 B 6 2 0.7459 2.4872 30 0.30 0.7663 Tukey-Kramer 1.0000 0.05 -4.3337 5.8254 -9.3521 10.8438
hospbi*age_gr*sample C 3 1 C 6 2 0.3912 2.7579 30 0.14 0.8881 Tukey-Kramer 1.0000 0.05 -5.2411 6.0235 -10.8055 11.5880
hospbi*age_gr*sample C 3 1 A 6 3 -0.8352 1.9724 30 -0.42 0.6750 Tukey-Kramer 1.0000 0.05 -4.8634 3.1930 -8.8430 7.1726
hospbi*age_gr*sample C 3 1 B 6 3 -1.6434 1.9851 30 -0.83 0.4143 Tukey-Kramer 1.0000 0.05 -5.6974 2.4107 -9.7027 6.4160
hospbi*age_gr*sample C 3 1 C 6 3 -1.2374 2.0847 30 -0.59 0.5573 Tukey-Kramer 1.0000 0.05 -5.4950 3.0202 -9.7014 7.2265
hospbi*age_gr*sample C 3 1 A 9 1 -3.3833 2.1275 30 -1.59 0.1223 Tukey-Kramer 0.9954 0.05 -7.7283 0.9617 -12.0209 5.2543
hospbi*age_gr*sample C 3 1 B 9 1 -2.3413 2.1481 30 -1.09 0.2844 Tukey-Kramer 1.0000 0.05 -6.7283 2.0456 -11.0624 6.3798
hospbi*age_gr*sample C 3 1 C 9 1 -3.2275 2.3074 30 -1.40 0.1721 Tukey-Kramer 0.9992 0.05 -7.9399 1.4848 -12.5954 6.1403
hospbi*age_gr*sample C 3 1 A 9 2 0.07002 2.9964 30 0.02 0.9815 Tukey-Kramer 1.0000 0.05 -6.0495 6.1895 -12.0953 12.2353
hospbi*age_gr*sample C 3 1 B 9 2 0.1348 3.0545 30 0.04 0.9651 Tukey-Kramer 1.0000 0.05 -6.1034 6.3729 -12.2664 12.5360
hospbi*age_gr*sample C 3 1 C 9 2 0.6954 3.4884 30 0.20 0.8433 Tukey-Kramer 1.0000 0.05 -6.4290 7.8197 -13.4675 14.8583
hospbi*age_gr*sample C 3 1 A 9 3 -1.7515 1.9453 30 -0.90 0.3751 Tukey-Kramer 1.0000 0.05 -5.7244 2.2214 -9.6495 6.1464
hospbi*age_gr*sample C 3 1 B 9 3 -2.1153 1.9566 30 -1.08 0.2883 Tukey-Kramer 1.0000 0.05 -6.1112 1.8806 -10.0590 5.8284
hospbi*age_gr*sample C 3 1 C 9 3 -3.6412 2.0453 30 -1.78 0.0852 Tukey-Kramer 0.9824 0.05 -7.8182 0.5359 -11.9449 4.6626
hospbi*age_gr*sample A 3 2 B 3 2 -1.9479 0.9195 30 -2.12 0.0425 Tukey-Kramer 0.9068 0.05 -3.8257 -0.07012 -5.6809 1.7850
hospbi*age_gr*sample A 3 2 C 3 2 -1.7300 0.9143 30 -1.89 0.0681 Tukey-Kramer 0.9665 0.05 -3.5971 0.1372 -5.4418 1.9818
hospbi*age_gr*sample A 3 2 A 3 3 1.8283 1.9262 30 0.95 0.3501 Tukey-Kramer 1.0000 0.05 -2.1055 5.7620 -5.9919 9.6484
hospbi*age_gr*sample A 3 2 B 3 3 1.8393 1.9375 30 0.95 0.3501 Tukey-Kramer 1.0000 0.05 -2.1177 5.7963 -6.0270 9.7056
hospbi*age_gr*sample A 3 2 C 3 3 1.5806 2.0271 30 0.78 0.4416 Tukey-Kramer 1.0000 0.05 -2.5592 5.7204 -6.6491 9.8103
hospbi*age_gr*sample A 3 2 A 6 1 0.6181 2.1100 30 0.29 0.7716 Tukey-Kramer 1.0000 0.05 -3.6912 4.9273 -7.9485 9.1846
hospbi*age_gr*sample A 3 2 B 6 1 -0.08749 2.1307 30 -0.04 0.9675 Tukey-Kramer 1.0000 0.05 -4.4390 4.2640 -8.7382 8.5632
hospbi*age_gr*sample A 3 2 C 6 1 0.3738 2.2912 30 0.16 0.8715 Tukey-Kramer 1.0000 0.05 -4.3056 5.0531 -8.9286 9.6761
hospbi*age_gr*sample A 3 2 A 6 2 2.1782 2.4364 30 0.89 0.3784 Tukey-Kramer 1.0000 0.05 -2.7977 7.1540 -7.7136 12.0699
hospbi*age_gr*sample A 3 2 B 6 2 2.2766 2.4722 30 0.92 0.3645 Tukey-Kramer 1.0000 0.05 -2.7724 7.3255 -7.7606 12.3137
hospbi*age_gr*sample A 3 2 C 6 2 1.9219 2.7444 30 0.70 0.4891 Tukey-Kramer 1.0000 0.05 -3.6828 7.5267 -9.2201 13.0639
hospbi*age_gr*sample A 3 2 A 6 3 0.6955 1.9535 30 0.36 0.7243 Tukey-Kramer 1.0000 0.05 -3.2941 4.6850 -7.2356 8.6265
hospbi*age_gr*sample A 3 2 B 6 3 -0.1127 1.9663 30 -0.06 0.9547 Tukey-Kramer 1.0000 0.05 -4.1284 3.9031 -8.0957 7.8704
hospbi*age_gr*sample A 3 2 C 6 3 0.2933 2.0669 30 0.14 0.8881 Tukey-Kramer 1.0000 0.05 -3.9278 4.5144 -8.0981 8.6846
hospbi*age_gr*sample A 3 2 A 9 1 -1.8526 2.1100 30 -0.88 0.3869 Tukey-Kramer 1.0000 0.05 -6.1618 2.4566 -10.4191 6.7139
hospbi*age_gr*sample A 3 2 B 9 1 -0.8106 2.1307 30 -0.38 0.7063 Tukey-Kramer 1.0000 0.05 -5.1622 3.5409 -9.4613 7.8400
hospbi*age_gr*sample A 3 2 C 9 1 -1.6969 2.2912 30 -0.74 0.4647 Tukey-Kramer 1.0000 0.05 -6.3762 2.9825 -10.9992 7.6055
hospbi*age_gr*sample A 3 2 A 9 2 1.6007 2.9840 30 0.54 0.5956 Tukey-Kramer 1.0000 0.05 -4.4934 7.6948 -10.5142 13.7156
hospbi*age_gr*sample A 3 2 B 9 2 1.6655 3.0423 30 0.55 0.5881 Tukey-Kramer 1.0000 0.05 -4.5478 7.8787 -10.6863 14.0172
hospbi*age_gr*sample A 3 2 C 9 2 2.2261 3.4778 30 0.64 0.5270 Tukey-Kramer 1.0000 0.05 -4.8765 9.3287 -11.8936 16.3457
hospbi*age_gr*sample A 3 2 A 9 3 -0.2208 1.9262 30 -0.11 0.9095 Tukey-Kramer 1.0000 0.05 -4.1546 3.7129 -8.0410 7.5993
hospbi*age_gr*sample A 3 2 B 9 3 -0.5846 1.9375 30 -0.30 0.7649 Tukey-Kramer 1.0000 0.05 -4.5416 3.3724 -8.4509 7.2817
hospbi*age_gr*sample A 3 2 C 9 3 -2.1105 2.0271 30 -1.04 0.3061 Tukey-Kramer 1.0000 0.05 -6.2503 2.0293 -10.3402 6.1193
hospbi*age_gr*sample B 3 2 C 3 2 0.2179 1.0473 30 0.21 0.8366 Tukey-Kramer 1.0000 0.05 -1.9208 2.3567 -4.0339 4.4698
hospbi*age_gr*sample B 3 2 A 3 3 3.7762 1.9713 30 1.92 0.0650 Tukey-Kramer 0.9622 0.05 -0.2497 7.8020 -4.2271 11.7794
hospbi*age_gr*sample B 3 2 B 3 3 3.7872 1.9824 30 1.91 0.0657 Tukey-Kramer 0.9631 0.05 -0.2614 7.8358 -4.2612 11.8356
hospbi*age_gr*sample B 3 2 C 3 3 3.5285 2.0700 30 1.70 0.0986 Tukey-Kramer 0.9892 0.05 -0.6989 7.7559 -4.8755 11.9324
hospbi*age_gr*sample B 3 2 A 6 1 2.5660 2.1513 30 1.19 0.2423 Tukey-Kramer 0.9999 0.05 -1.8275 6.9594 -6.1680 11.3000
hospbi*age_gr*sample B 3 2 B 6 1 1.8604 2.1716 30 0.86 0.3984 Tukey-Kramer 1.0000 0.05 -2.5746 6.2954 -6.9561 10.6770
hospbi*age_gr*sample B 3 2 C 6 1 2.3217 2.3293 30 1.00 0.3269 Tukey-Kramer 1.0000 0.05 -2.4354 7.0787 -7.1351 11.7785
hospbi*age_gr*sample B 3 2 A 6 2 4.1261 2.4722 30 1.67 0.1055 Tukey-Kramer 0.9916 0.05 -0.9229 9.1751 -5.9111 14.1633
hospbi*age_gr*sample B 3 2 B 6 2 4.2245 2.5075 30 1.68 0.1024 Tukey-Kramer 0.9906 0.05 -0.8966 9.3456 -5.9560 14.4050
hospbi*age_gr*sample B 3 2 C 6 2 3.8698 2.7762 30 1.39 0.1736 Tukey-Kramer 0.9993 0.05 -1.8000 9.5396 -7.4015 15.1411
hospbi*age_gr*sample B 3 2 A 6 3 2.6434 1.9980 30 1.32 0.1958 Tukey-Kramer 0.9997 0.05 -1.4370 6.7238 -5.4683 10.7551
hospbi*age_gr*sample B 3 2 B 6 3 1.8352 2.0105 30 0.91 0.3686 Tukey-Kramer 1.0000 0.05 -2.2708 5.9413 -6.3273 9.9978
hospbi*age_gr*sample B 3 2 C 6 3 2.2412 2.1090 30 1.06 0.2964 Tukey-Kramer 1.0000 0.05 -2.0659 6.5483 -6.3211 10.8035
hospbi*age_gr*sample B 3 2 A 9 1 0.09529 2.1513 30 0.04 0.9650 Tukey-Kramer 1.0000 0.05 -4.2982 4.4888 -8.6387 8.8293
hospbi*age_gr*sample B 3 2 B 9 1 1.1373 2.1716 30 0.52 0.6043 Tukey-Kramer 1.0000 0.05 -3.2977 5.5723 -7.6793 9.9538
hospbi*age_gr*sample B 3 2 C 9 1 0.2511 2.3293 30 0.11 0.9149 Tukey-Kramer 1.0000 0.05 -4.5060 5.0081 -9.2058 9.7079
hospbi*age_gr*sample B 3 2 A 9 2 3.5486 3.0133 30 1.18 0.2482 Tukey-Kramer 1.0000 0.05 -2.6054 9.7026 -8.6853 15.7825
hospbi*age_gr*sample B 3 2 B 9 2 3.6134 3.0711 30 1.18 0.2486 Tukey-Kramer 1.0000 0.05 -2.6587 9.8854 -8.8552 16.0819
hospbi*age_gr*sample B 3 2 C 9 2 4.1740 3.5030 30 1.19 0.2428 Tukey-Kramer 0.9999 0.05 -2.9800 11.3280 -10.0479 18.3959
hospbi*age_gr*sample B 3 2 A 9 3 1.7271 1.9713 30 0.88 0.3879 Tukey-Kramer 1.0000 0.05 -2.2988 5.7529 -6.2762 9.7303
hospbi*age_gr*sample B 3 2 B 9 3 1.3633 1.9824 30 0.69 0.4969 Tukey-Kramer 1.0000 0.05 -2.6853 5.4119 -6.6851 9.4117
hospbi*age_gr*sample B 3 2 C 9 3 -0.1626 2.0700 30 -0.08 0.9379 Tukey-Kramer 1.0000 0.05 -4.3900 4.0649 -8.5665 8.2414
hospbi*age_gr*sample C 3 2 A 3 3 3.5582 2.3034 30 1.54 0.1329 Tukey-Kramer 0.9969 0.05 -1.1459 8.2623 -5.7933 12.9098
hospbi*age_gr*sample C 3 2 B 3 3 3.5693 2.3129 30 1.54 0.1333 Tukey-Kramer 0.9969 0.05 -1.1543 8.2928 -5.8209 12.9595
hospbi*age_gr*sample C 3 2 C 3 3 3.3106 2.3884 30 1.39 0.1759 Tukey-Kramer 0.9993 0.05 -1.5672 8.1883 -6.3861 13.0072
hospbi*age_gr*sample C 3 2 A 6 1 2.3480 2.4592 30 0.95 0.3473 Tukey-Kramer 1.0000 0.05 -2.6743 7.3703 -7.6361 12.3321
hospbi*age_gr*sample C 3 2 B 6 1 1.6425 2.4770 30 0.66 0.5123 Tukey-Kramer 1.0000 0.05 -3.4162 6.7011 -8.4139 11.6989
hospbi*age_gr*sample C 3 2 C 6 1 2.1037 2.6163 30 0.80 0.4277 Tukey-Kramer 1.0000 0.05 -3.2395 7.4470 -8.5184 12.7259
hospbi*age_gr*sample C 3 2 A 6 2 3.9082 2.7444 30 1.42 0.1647 Tukey-Kramer 0.9990 0.05 -1.6966 9.5129 -7.2338 15.0501
hospbi*age_gr*sample C 3 2 B 6 2 4.0065 2.7762 30 1.44 0.1593 Tukey-Kramer 0.9988 0.05 -1.6633 9.6763 -7.2648 15.2778
hospbi*age_gr*sample C 3 2 C 6 2 3.6519 3.0211 30 1.21 0.2362 Tukey-Kramer 0.9999 0.05 -2.5180 9.8217 -8.6136 15.9173
hospbi*age_gr*sample C 3 2 A 6 3 2.4255 2.3263 30 1.04 0.3054 Tukey-Kramer 1.0000 0.05 -2.3254 7.1763 -7.0190 11.8700
hospbi*age_gr*sample C 3 2 B 6 3 1.6173 2.3370 30 0.69 0.4942 Tukey-Kramer 1.0000 0.05 -3.1555 6.3902 -7.8709 11.1055
hospbi*age_gr*sample C 3 2 C 6 3 2.0233 2.4223 30 0.84 0.4102 Tukey-Kramer 1.0000 0.05 -2.9236 6.9702 -7.8110 11.8575
hospbi*age_gr*sample C 3 2 A 9 1 -0.1227 2.4592 30 -0.05 0.9606 Tukey-Kramer 1.0000 0.05 -5.1449 4.8996 -10.1067 9.8614
hospbi*age_gr*sample C 3 2 B 9 1 0.9193 2.4770 30 0.37 0.7131 Tukey-Kramer 1.0000 0.05 -4.1393 5.9780 -9.1371 10.9757
hospbi*age_gr*sample C 3 2 C 9 1 0.03311 2.6163 30 0.01 0.9900 Tukey-Kramer 1.0000 0.05 -5.3102 5.3764 -10.5891 10.6553
hospbi*age_gr*sample C 3 2 A 9 2 3.3307 3.2403 30 1.03 0.3122 Tukey-Kramer 1.0000 0.05 -3.2869 9.9483 -9.8248 16.4862
hospbi*age_gr*sample C 3 2 B 9 2 3.3954 3.2941 30 1.03 0.3109 Tukey-Kramer 1.0000 0.05 -3.3321 10.1229 -9.9785 16.7694
hospbi*age_gr*sample C 3 2 C 9 2 3.9561 3.7001 30 1.07 0.2935 Tukey-Kramer 1.0000 0.05 -3.6005 11.5126 -11.0660 18.9781
hospbi*age_gr*sample C 3 2 A 9 3 1.5091 2.3034 30 0.66 0.5173 Tukey-Kramer 1.0000 0.05 -3.1950 6.2132 -7.8424 10.8607
hospbi*age_gr*sample C 3 2 B 9 3 1.1454 2.3129 30 0.50 0.6241 Tukey-Kramer 1.0000 0.05 -3.5782 5.8689 -8.2448 10.5356
hospbi*age_gr*sample C 3 2 C 9 3 -0.3805 2.3884 30 -0.16 0.8745 Tukey-Kramer 1.0000 0.05 -5.2582 4.4972 -10.0772 9.3162
hospbi*age_gr*sample A 3 3 B 3 3 0.01104 0.4597 30 0.02 0.9810 Tukey-Kramer 1.0000 0.05 -0.9279 0.9499 -1.8554 1.8775
hospbi*age_gr*sample A 3 3 C 3 3 -0.2477 0.4571 30 -0.54 0.5919 Tukey-Kramer 1.0000 0.05 -1.1813 0.6859 -2.1036 1.6082
hospbi*age_gr*sample A 3 3 A 6 1 -1.2102 1.4920 30 -0.81 0.4237 Tukey-Kramer 1.0000 0.05 -4.2573 1.8369 -7.2677 4.8472
hospbi*age_gr*sample A 3 3 B 6 1 -1.9158 1.5212 30 -1.26 0.2176 Tukey-Kramer 0.9998 0.05 -5.0224 1.1909 -8.0916 4.2601
hospbi*age_gr*sample A 3 3 C 6 1 -1.4545 1.7389 30 -0.84 0.4095 Tukey-Kramer 1.0000 0.05 -5.0058 2.0968 -8.5143 5.6053
hospbi*age_gr*sample A 3 3 A 6 2 0.3499 1.9262 30 0.18 0.8571 Tukey-Kramer 1.0000 0.05 -3.5838 4.2837 -7.4702 8.1700
hospbi*age_gr*sample A 3 3 B 6 2 0.4483 1.9713 30 0.23 0.8216 Tukey-Kramer 1.0000 0.05 -3.5776 4.4742 -7.5550 8.4515
hospbi*age_gr*sample A 3 3 C 6 2 0.09364 2.3034 30 0.04 0.9678 Tukey-Kramer 1.0000 0.05 -4.6105 4.7977 -9.2579 9.4452
hospbi*age_gr*sample A 3 3 A 6 3 -1.1328 1.2610 30 -0.90 0.3762 Tukey-Kramer 1.0000 0.05 -3.7080 1.4425 -6.2522 3.9867
hospbi*age_gr*sample A 3 3 B 6 3 -1.9409 1.2807 30 -1.52 0.1401 Tukey-Kramer 0.9976 0.05 -4.5565 0.6747 -7.1406 3.2588
hospbi*age_gr*sample A 3 3 C 6 3 -1.5350 1.4303 30 -1.07 0.2918 Tukey-Kramer 1.0000 0.05 -4.4561 1.3862 -7.3421 4.2721
hospbi*age_gr*sample A 3 3 A 9 1 -3.6809 1.4920 30 -2.47 0.0196 Tukey-Kramer 0.7350 0.05 -6.7280 -0.6338 -9.7383 2.3766
hospbi*age_gr*sample A 3 3 B 9 1 -2.6389 1.5212 30 -1.73 0.0930 Tukey-Kramer 0.9868 0.05 -5.7456 0.4677 -8.8148 3.5370
hospbi*age_gr*sample A 3 3 C 9 1 -3.5251 1.7389 30 -2.03 0.0516 Tukey-Kramer 0.9358 0.05 -7.0764 0.02617 -10.5849 3.5347
hospbi*age_gr*sample A 3 3 A 9 2 -0.2276 2.5842 30 -0.09 0.9304 Tukey-Kramer 1.0000 0.05 -5.5052 5.0501 -10.7194 10.2642
hospbi*age_gr*sample A 3 3 B 9 2 -0.1628 2.6514 30 -0.06 0.9514 Tukey-Kramer 1.0000 0.05 -5.5776 5.2520 -10.9273 10.6016
hospbi*age_gr*sample A 3 3 C 9 2 0.3978 3.1415 30 0.13 0.9001 Tukey-Kramer 1.0000 0.05 -6.0180 6.8136 -12.3565 13.1521
hospbi*age_gr*sample A 3 3 A 9 3 -2.0491 1.2182 30 -1.68 0.1029 Tukey-Kramer 0.9908 0.05 -4.5370 0.4388 -6.9950 2.8968
hospbi*age_gr*sample A 3 3 B 9 3 -2.4129 1.2361 30 -1.95 0.0603 Tukey-Kramer 0.9546 0.05 -4.9374 0.1116 -7.4314 2.6057
hospbi*age_gr*sample A 3 3 C 9 3 -3.9387 1.3722 30 -2.87 0.0074 Tukey-Kramer 0.4744 0.05 -6.7411 -1.1364 -9.5097 1.6323
hospbi*age_gr*sample B 3 3 C 3 3 -0.2587 0.5236 30 -0.49 0.6248 Tukey-Kramer 1.0000 0.05 -1.3281 0.8107 -2.3846 1.8672
hospbi*age_gr*sample B 3 3 A 6 1 -1.2213 1.5067 30 -0.81 0.4240 Tukey-Kramer 1.0000 0.05 -4.2983 1.8558 -7.3382 4.8957
hospbi*age_gr*sample B 3 3 B 6 1 -1.9268 1.5356 30 -1.25 0.2192 Tukey-Kramer 0.9999 0.05 -5.0628 1.2092 -8.1611 4.3075
hospbi*age_gr*sample B 3 3 C 6 1 -1.4655 1.7515 30 -0.84 0.4094 Tukey-Kramer 1.0000 0.05 -5.0426 2.1115 -8.5765 5.6454
hospbi*age_gr*sample B 3 3 A 6 2 0.3389 1.9375 30 0.17 0.8623 Tukey-Kramer 1.0000 0.05 -3.6181 4.2959 -7.5274 8.2052
hospbi*age_gr*sample B 3 3 B 6 2 0.4372 1.9824 30 0.22 0.8269 Tukey-Kramer 1.0000 0.05 -3.6113 4.4858 -7.6111 8.4856
hospbi*age_gr*sample B 3 3 C 6 2 0.08260 2.3129 30 0.04 0.9717 Tukey-Kramer 1.0000 0.05 -4.6409 4.8061 -9.3076 9.4728
hospbi*age_gr*sample B 3 3 A 6 3 -1.1438 1.2783 30 -0.89 0.3780 Tukey-Kramer 1.0000 0.05 -3.7544 1.4668 -6.3336 4.0459
hospbi*age_gr*sample B 3 3 B 6 3 -1.9520 1.2978 30 -1.50 0.1430 Tukey-Kramer 0.9978 0.05 -4.6024 0.6984 -7.2209 3.3169
hospbi*age_gr*sample B 3 3 C 6 3 -1.5460 1.4456 30 -1.07 0.2934 Tukey-Kramer 1.0000 0.05 -4.4984 1.4063 -7.4152 4.3231
hospbi*age_gr*sample B 3 3 A 9 1 -3.6919 1.5067 30 -2.45 0.0203 Tukey-Kramer 0.7450 0.05 -6.7689 -0.6149 -9.8089 2.4250
hospbi*age_gr*sample B 3 3 B 9 1 -2.6499 1.5356 30 -1.73 0.0947 Tukey-Kramer 0.9876 0.05 -5.7860 0.4861 -8.8842 3.5843
hospbi*age_gr*sample B 3 3 C 9 1 -3.5362 1.7515 30 -2.02 0.0525 Tukey-Kramer 0.9381 0.05 -7.1132 0.04084 -10.6471 3.5748
hospbi*age_gr*sample B 3 3 A 9 2 -0.2386 2.5927 30 -0.09 0.9273 Tukey-Kramer 1.0000 0.05 -5.5336 5.0564 -10.7649 10.2877
hospbi*age_gr*sample B 3 3 B 9 2 -0.1739 2.6597 30 -0.07 0.9483 Tukey-Kramer 1.0000 0.05 -5.6056 5.2579 -10.9719 10.6242
hospbi*age_gr*sample B 3 3 C 9 2 0.3868 3.1485 30 0.12 0.9030 Tukey-Kramer 1.0000 0.05 -6.0433 6.8168 -12.3959 13.1694
hospbi*age_gr*sample B 3 3 A 9 3 -2.0602 1.2361 30 -1.67 0.1060 Tukey-Kramer 0.9918 0.05 -4.5847 0.4643 -7.0787 2.9584
hospbi*age_gr*sample B 3 3 B 9 3 -2.4239 1.2538 30 -1.93 0.0627 Tukey-Kramer 0.9586 0.05 -4.9844 0.1366 -7.5142 2.6663
hospbi*age_gr*sample B 3 3 C 9 3 -3.9498 1.3881 30 -2.85 0.0079 Tukey-Kramer 0.4903 0.05 -6.7847 -1.1149 -9.5854 1.6859
hospbi*age_gr*sample C 3 3 A 6 1 -0.9625 1.6202 30 -0.59 0.5569 Tukey-Kramer 1.0000 0.05 -4.2713 2.3463 -7.5403 5.6152
hospbi*age_gr*sample C 3 3 B 6 1 -1.6681 1.6471 30 -1.01 0.3193 Tukey-Kramer 1.0000 0.05 -5.0318 1.6957 -8.3551 5.0189
hospbi*age_gr*sample C 3 3 C 6 1 -1.2068 1.8500 30 -0.65 0.5192 Tukey-Kramer 1.0000 0.05 -4.9851 2.5714 -8.7178 6.3042
hospbi*age_gr*sample C 3 3 A 6 2 0.5976 2.0271 30 0.29 0.7702 Tukey-Kramer 1.0000 0.05 -3.5422 4.7374 -7.6321 8.8273
hospbi*age_gr*sample C 3 3 B 6 2 0.6960 2.0700 30 0.34 0.7390 Tukey-Kramer 1.0000 0.05 -3.5315 4.9234 -7.7080 9.0999
hospbi*age_gr*sample C 3 3 C 6 2 0.3413 2.3884 30 0.14 0.8873 Tukey-Kramer 1.0000 0.05 -4.5364 5.2190 -9.3554 10.0380
hospbi*age_gr*sample C 3 3 A 6 3 -0.8851 1.4103 30 -0.63 0.5350 Tukey-Kramer 1.0000 0.05 -3.7653 1.9951 -6.6108 4.8406
hospbi*age_gr*sample C 3 3 B 6 3 -1.6933 1.4280 30 -1.19 0.2450 Tukey-Kramer 0.9999 0.05 -4.6096 1.2231 -7.4908 4.1043
hospbi*age_gr*sample C 3 3 C 6 3 -1.2873 1.5636 30 -0.82 0.4168 Tukey-Kramer 1.0000 0.05 -4.4805 1.9059 -7.6353 5.0607
hospbi*age_gr*sample C 3 3 A 9 1 -3.4332 1.6202 30 -2.12 0.0425 Tukey-Kramer 0.9066 0.05 -6.7420 -0.1244 -10.0110 3.1445
hospbi*age_gr*sample C 3 3 B 9 1 -2.3912 1.6471 30 -1.45 0.1569 Tukey-Kramer 0.9987 0.05 -5.7550 0.9725 -9.0782 4.2958
hospbi*age_gr*sample C 3 3 C 9 1 -3.2774 1.8500 30 -1.77 0.0866 Tukey-Kramer 0.9833 0.05 -7.0557 0.5008 -10.7885 4.2336
hospbi*age_gr*sample C 3 3 A 9 2 0.02011 2.6603 30 0.01 0.9940 Tukey-Kramer 1.0000 0.05 -5.4129 5.4531 -10.7804 10.8207
hospbi*age_gr*sample C 3 3 B 9 2 0.08486 2.7256 30 0.03 0.9754 Tukey-Kramer 1.0000 0.05 -5.4815 5.6512 -10.9807 11.1505
hospbi*age_gr*sample C 3 3 C 9 2 0.6455 3.2043 30 0.20 0.8417 Tukey-Kramer 1.0000 0.05 -5.8986 7.1896 -12.3640 13.6549
hospbi*age_gr*sample C 3 3 A 9 3 -1.8014 1.3722 30 -1.31 0.1992 Tukey-Kramer 0.9997 0.05 -4.6038 1.0009 -7.3724 3.7696
hospbi*age_gr*sample C 3 3 B 9 3 -2.1652 1.3881 30 -1.56 0.1293 Tukey-Kramer 0.9964 0.05 -5.0001 0.6697 -7.8008 3.4705
hospbi*age_gr*sample C 3 3 C 9 3 -3.6911 1.5105 30 -2.44 0.0206 Tukey-Kramer 0.7491 0.05 -6.7760 -0.6061 -9.8238 2.4417
hospbi*age_gr*sample A 6 1 B 6 1 -0.7055 0.6502 30 -1.09 0.2865 Tukey-Kramer 1.0000 0.05 -2.0333 0.6223 -3.3451 1.9341
hospbi*age_gr*sample A 6 1 C 6 1 -0.2443 0.6465 30 -0.38 0.7082 Tukey-Kramer 1.0000 0.05 -1.5646 1.0760 -2.8689 2.3804
hospbi*age_gr*sample A 6 1 A 6 2 1.5601 2.1100 30 0.74 0.4654 Tukey-Kramer 1.0000 0.05 -2.7491 5.8693 -7.0064 10.1266
hospbi*age_gr*sample A 6 1 B 6 2 1.6585 2.1513 30 0.77 0.4468 Tukey-Kramer 1.0000 0.05 -2.7350 6.0520 -7.0755 10.3925
hospbi*age_gr*sample A 6 1 C 6 2 1.3039 2.4592 30 0.53 0.5999 Tukey-Kramer 1.0000 0.05 -3.7184 6.3261 -8.6802 11.2879
hospbi*age_gr*sample A 6 1 A 6 3 0.07743 1.5271 30 0.05 0.9599 Tukey-Kramer 1.0000 0.05 -3.0413 3.1962 -6.1226 6.2774
hospbi*age_gr*sample A 6 1 B 6 3 -0.7307 1.5435 30 -0.47 0.6393 Tukey-Kramer 1.0000 0.05 -3.8829 2.4215 -6.9971 5.5357
hospbi*age_gr*sample A 6 1 C 6 3 -0.3248 1.6697 30 -0.19 0.8471 Tukey-Kramer 1.0000 0.05 -3.7347 3.0852 -7.1037 6.4541
hospbi*age_gr*sample A 6 1 A 9 1 -2.4707 1.7228 30 -1.43 0.1619 Tukey-Kramer 0.9989 0.05 -5.9891 1.0478 -9.4652 4.5239
hospbi*age_gr*sample A 6 1 B 9 1 -1.4287 1.7481 30 -0.82 0.4202 Tukey-Kramer 1.0000 0.05 -4.9989 2.1415 -8.5260 5.6687
hospbi*age_gr*sample A 6 1 C 9 1 -2.3149 1.9406 30 -1.19 0.2423 Tukey-Kramer 0.9999 0.05 -6.2781 1.6482 -10.1935 5.5637
hospbi*age_gr*sample A 6 1 A 9 2 0.9826 2.7240 30 0.36 0.7208 Tukey-Kramer 1.0000 0.05 -4.5805 6.5458 -10.0767 12.0420
hospbi*age_gr*sample A 6 1 B 9 2 1.0474 2.7878 30 0.38 0.7098 Tukey-Kramer 1.0000 0.05 -4.6460 6.7408 -10.2709 12.3657
hospbi*age_gr*sample A 6 1 C 9 2 1.6080 3.2574 30 0.49 0.6252 Tukey-Kramer 1.0000 0.05 -5.0446 8.2606 -11.6170 14.8331
hospbi*age_gr*sample A 6 1 A 9 3 -0.8389 1.4920 30 -0.56 0.5781 Tukey-Kramer 1.0000 0.05 -3.8860 2.2082 -6.8963 5.2185
hospbi*age_gr*sample A 6 1 B 9 3 -1.2026 1.5067 30 -0.80 0.4310 Tukey-Kramer 1.0000 0.05 -4.2797 1.8744 -7.3196 4.9143
hospbi*age_gr*sample A 6 1 C 9 3 -2.7285 1.6202 30 -1.68 0.1025 Tukey-Kramer 0.9907 0.05 -6.0373 0.5803 -9.3063 3.8492
hospbi*age_gr*sample B 6 1 C 6 1 0.4613 0.7405 30 0.62 0.5381 Tukey-Kramer 1.0000 0.05 -1.0511 1.9736 -2.5452 3.4677
hospbi*age_gr*sample B 6 1 A 6 2 2.2657 2.1307 30 1.06 0.2961 Tukey-Kramer 1.0000 0.05 -2.0859 6.6172 -6.3850 10.9163
hospbi*age_gr*sample B 6 1 B 6 2 2.3640 2.1716 30 1.09 0.2850 Tukey-Kramer 1.0000 0.05 -2.0709 6.7990 -6.4525 11.1806
hospbi*age_gr*sample B 6 1 C 6 2 2.0094 2.4770 30 0.81 0.4236 Tukey-Kramer 1.0000 0.05 -3.0493 7.0681 -8.0470 12.0658
hospbi*age_gr*sample B 6 1 A 6 3 0.7830 1.5556 30 0.50 0.6184 Tukey-Kramer 1.0000 0.05 -2.3940 3.9600 -5.5328 7.0987
hospbi*age_gr*sample B 6 1 B 6 3 -0.02517 1.5717 30 -0.02 0.9873 Tukey-Kramer 1.0000 0.05 -3.2350 3.1846 -6.4061 6.3558
hospbi*age_gr*sample B 6 1 C 6 3 0.3808 1.6958 30 0.22 0.8239 Tukey-Kramer 1.0000 0.05 -3.0825 3.8441 -6.5042 7.2657
hospbi*age_gr*sample B 6 1 A 9 1 -1.7651 1.7481 30 -1.01 0.3207 Tukey-Kramer 1.0000 0.05 -5.3353 1.8050 -8.8625 5.3322
hospbi*age_gr*sample B 6 1 B 9 1 -0.7231 1.7731 30 -0.41 0.6863 Tukey-Kramer 1.0000 0.05 -4.3443 2.8980 -7.9218 6.4756
hospbi*age_gr*sample B 6 1 C 9 1 -1.6094 1.9631 30 -0.82 0.4188 Tukey-Kramer 1.0000 0.05 -5.6185 2.3998 -9.5794 6.3606
hospbi*age_gr*sample B 6 1 A 9 2 1.6882 2.7401 30 0.62 0.5425 Tukey-Kramer 1.0000 0.05 -3.9078 7.2842 -9.4364 12.8128
hospbi*age_gr*sample B 6 1 B 9 2 1.7529 2.8035 30 0.63 0.5365 Tukey-Kramer 1.0000 0.05 -3.9726 7.4785 -9.6292 13.1351
hospbi*age_gr*sample B 6 1 C 9 2 2.3136 3.2709 30 0.71 0.4848 Tukey-Kramer 1.0000 0.05 -4.3665 8.9937 -10.9662 15.5933
hospbi*age_gr*sample B 6 1 A 9 3 -0.1334 1.5212 30 -0.09 0.9307 Tukey-Kramer 1.0000 0.05 -3.2400 2.9733 -6.3092 6.0425
hospbi*age_gr*sample B 6 1 B 9 3 -0.4971 1.5356 30 -0.32 0.7484 Tukey-Kramer 1.0000 0.05 -3.6331 2.6389 -6.7314 5.7372
hospbi*age_gr*sample B 6 1 C 9 3 -2.0230 1.6471 30 -1.23 0.2289 Tukey-Kramer 0.9999 0.05 -5.3867 1.3408 -8.7100 4.6640
hospbi*age_gr*sample C 6 1 A 6 2 1.8044 2.2912 30 0.79 0.4372 Tukey-Kramer 1.0000 0.05 -2.8749 6.4838 -7.4979 11.1068
hospbi*age_gr*sample C 6 1 B 6 2 1.9028 2.3293 30 0.82 0.4204 Tukey-Kramer 1.0000 0.05 -2.8543 6.6598 -7.5540 11.3596
hospbi*age_gr*sample C 6 1 C 6 2 1.5481 2.6163 30 0.59 0.5585 Tukey-Kramer 1.0000 0.05 -3.7951 6.8914 -9.0740 12.1703
hospbi*age_gr*sample C 6 1 A 6 3 0.3217 1.7691 30 0.18 0.8569 Tukey-Kramer 1.0000 0.05 -3.2913 3.9347 -6.8608 7.5042
hospbi*age_gr*sample C 6 1 B 6 3 -0.4864 1.7833 30 -0.27 0.7869 Tukey-Kramer 1.0000 0.05 -4.1283 3.1555 -7.7263 6.7535
hospbi*age_gr*sample C 6 1 C 6 3 -0.08048 1.8936 30 -0.04 0.9664 Tukey-Kramer 1.0000 0.05 -3.9477 3.7867 -7.7682 7.6073
hospbi*age_gr*sample C 6 1 A 9 1 -2.2264 1.9406 30 -1.15 0.2603 Tukey-Kramer 1.0000 0.05 -6.1895 1.7368 -10.1050 5.6522
hospbi*age_gr*sample C 6 1 B 9 1 -1.1844 1.9631 30 -0.60 0.5508 Tukey-Kramer 1.0000 0.05 -5.1935 2.8247 -9.1544 6.7856
hospbi*age_gr*sample C 6 1 C 9 1 -2.0706 2.1362 30 -0.97 0.3401 Tukey-Kramer 1.0000 0.05 -6.4334 2.2921 -10.7436 6.6023
hospbi*age_gr*sample C 6 1 A 9 2 1.2269 2.8667 30 0.43 0.6717 Tukey-Kramer 1.0000 0.05 -4.6276 7.0815 -10.4117 12.8655
hospbi*age_gr*sample C 6 1 B 9 2 1.2917 2.9274 30 0.44 0.6622 Tukey-Kramer 1.0000 0.05 -4.6868 7.2702 -10.5933 13.1767
hospbi*age_gr*sample C 6 1 C 9 2 1.8523 3.3777 30 0.55 0.5875 Tukey-Kramer 1.0000 0.05 -5.0458 8.7504 -11.8609 15.5655
hospbi*age_gr*sample C 6 1 A 9 3 -0.5946 1.7389 30 -0.34 0.7348 Tukey-Kramer 1.0000 0.05 -4.1459 2.9567 -7.6544 6.4652
hospbi*age_gr*sample C 6 1 B 9 3 -0.9584 1.7515 30 -0.55 0.5883 Tukey-Kramer 1.0000 0.05 -4.5354 2.6187 -8.0693 6.1526
hospbi*age_gr*sample C 6 1 C 9 3 -2.4842 1.8500 30 -1.34 0.1894 Tukey-Kramer 0.9996 0.05 -6.2625 1.2940 -9.9952 5.0268
hospbi*age_gr*sample A 6 2 B 6 2 0.09837 0.9195 30 0.11 0.9155 Tukey-Kramer 1.0000 0.05 -1.7794 1.9762 -3.6346 3.8313
hospbi*age_gr*sample A 6 2 C 6 2 -0.2563 0.9143 30 -0.28 0.7812 Tukey-Kramer 1.0000 0.05 -2.1234 1.6109 -3.9681 3.4555
hospbi*age_gr*sample A 6 2 A 6 3 -1.4827 1.9535 30 -0.76 0.4538 Tukey-Kramer 1.0000 0.05 -5.4722 2.5069 -9.4138 6.4484
hospbi*age_gr*sample A 6 2 B 6 3 -2.2908 1.9663 30 -1.17 0.2532 Tukey-Kramer 1.0000 0.05 -6.3066 1.7249 -10.2739 5.6922
hospbi*age_gr*sample A 6 2 C 6 3 -1.8849 2.0669 30 -0.91 0.3691 Tukey-Kramer 1.0000 0.05 -6.1060 2.3362 -10.2763 6.5065
hospbi*age_gr*sample A 6 2 A 9 1 -4.0308 2.1100 30 -1.91 0.0657 Tukey-Kramer 0.9632 0.05 -8.3400 0.2784 -12.5973 4.5357
hospbi*age_gr*sample A 6 2 B 9 1 -2.9888 2.1307 30 -1.40 0.1710 Tukey-Kramer 0.9992 0.05 -7.3404 1.3627 -11.6395 5.6618
hospbi*age_gr*sample A 6 2 C 9 1 -3.8750 2.2912 30 -1.69 0.1012 Tukey-Kramer 0.9902 0.05 -8.5544 0.8043 -13.1774 5.4273
hospbi*age_gr*sample A 6 2 A 9 2 -0.5775 2.9840 30 -0.19 0.8479 Tukey-Kramer 1.0000 0.05 -6.6716 5.5167 -12.6924 11.5374
hospbi*age_gr*sample A 6 2 B 9 2 -0.5127 3.0423 30 -0.17 0.8673 Tukey-Kramer 1.0000 0.05 -6.7260 5.7006 -12.8645 11.8390
hospbi*age_gr*sample A 6 2 C 9 2 0.04790 3.4778 30 0.01 0.9891 Tukey-Kramer 1.0000 0.05 -7.0547 7.1505 -14.0717 14.1675
hospbi*age_gr*sample A 6 2 A 9 3 -2.3990 1.9262 30 -1.25 0.2226 Tukey-Kramer 0.9999 0.05 -6.3328 1.5347 -10.2192 5.4211
hospbi*age_gr*sample A 6 2 B 9 3 -2.7628 1.9375 30 -1.43 0.1642 Tukey-Kramer 0.9990 0.05 -6.7198 1.1942 -10.6291 5.1035
hospbi*age_gr*sample A 6 2 C 9 3 -4.2887 2.0271 30 -2.12 0.0428 Tukey-Kramer 0.9078 0.05 -8.4285 -0.1489 -12.5184 3.9411
hospbi*age_gr*sample B 6 2 C 6 2 -0.3546 1.0473 30 -0.34 0.7372 Tukey-Kramer 1.0000 0.05 -2.4934 1.7841 -4.6065 3.8972
hospbi*age_gr*sample B 6 2 A 6 3 -1.5811 1.9980 30 -0.79 0.4350 Tukey-Kramer 1.0000 0.05 -5.6615 2.4993 -9.6928 6.5306
hospbi*age_gr*sample B 6 2 B 6 3 -2.3892 2.0105 30 -1.19 0.2440 Tukey-Kramer 0.9999 0.05 -6.4952 1.7168 -10.5518 5.7733
hospbi*age_gr*sample B 6 2 C 6 3 -1.9833 2.1090 30 -0.94 0.3545 Tukey-Kramer 1.0000 0.05 -6.2904 2.3238 -10.5456 6.5790
hospbi*age_gr*sample B 6 2 A 9 1 -4.1292 2.1513 30 -1.92 0.0645 Tukey-Kramer 0.9614 0.05 -8.5226 0.2643 -12.8632 4.6048
hospbi*age_gr*sample B 6 2 B 9 1 -3.0872 2.1716 30 -1.42 0.1654 Tukey-Kramer 0.9990 0.05 -7.5222 1.3478 -11.9038 5.7294
hospbi*age_gr*sample B 6 2 C 9 1 -3.9734 2.3293 30 -1.71 0.0984 Tukey-Kramer 0.9891 0.05 -8.7305 0.7836 -13.4302 5.4834
hospbi*age_gr*sample B 6 2 A 9 2 -0.6759 3.0133 30 -0.22 0.8241 Tukey-Kramer 1.0000 0.05 -6.8299 5.4782 -12.9097 11.5580
hospbi*age_gr*sample B 6 2 B 9 2 -0.6111 3.0711 30 -0.20 0.8436 Tukey-Kramer 1.0000 0.05 -6.8831 5.6609 -13.0796 11.8574
hospbi*age_gr*sample B 6 2 C 9 2 -0.05047 3.5030 30 -0.01 0.9886 Tukey-Kramer 1.0000 0.05 -7.2045 7.1036 -14.2724 14.1714
hospbi*age_gr*sample B 6 2 A 9 3 -2.4974 1.9713 30 -1.27 0.2149 Tukey-Kramer 0.9998 0.05 -6.5233 1.5285 -10.5007 5.5059
hospbi*age_gr*sample B 6 2 B 9 3 -2.8611 1.9824 30 -1.44 0.1593 Tukey-Kramer 0.9988 0.05 -6.9097 1.1874 -10.9095 5.1872
hospbi*age_gr*sample B 6 2 C 9 3 -4.3870 2.0700 30 -2.12 0.0424 Tukey-Kramer 0.9065 0.05 -8.6145 -0.1596 -12.7910 4.0169
hospbi*age_gr*sample C 6 2 A 6 3 -1.2264 2.3263 30 -0.53 0.6019 Tukey-Kramer 1.0000 0.05 -5.9773 3.5244 -10.6709 8.2181
hospbi*age_gr*sample C 6 2 B 6 3 -2.0346 2.3370 30 -0.87 0.3909 Tukey-Kramer 1.0000 0.05 -6.8074 2.7383 -11.5228 7.4537
hospbi*age_gr*sample C 6 2 C 6 3 -1.6286 2.4223 30 -0.67 0.5065 Tukey-Kramer 1.0000 0.05 -6.5755 3.3183 -11.4628 8.2056
hospbi*age_gr*sample C 6 2 A 9 1 -3.7745 2.4592 30 -1.53 0.1353 Tukey-Kramer 0.9971 0.05 -8.7968 1.2478 -13.7586 6.2096
hospbi*age_gr*sample C 6 2 B 9 1 -2.7325 2.4770 30 -1.10 0.2787 Tukey-Kramer 1.0000 0.05 -7.7912 2.3261 -12.7889 7.3238
hospbi*age_gr*sample C 6 2 C 9 1 -3.6188 2.6163 30 -1.38 0.1768 Tukey-Kramer 0.9993 0.05 -8.9620 1.7245 -14.2409 7.0034
hospbi*age_gr*sample C 6 2 A 9 2 -0.3212 3.2403 30 -0.10 0.9217 Tukey-Kramer 1.0000 0.05 -6.9388 6.2964 -13.4767 12.8343
hospbi*age_gr*sample C 6 2 B 9 2 -0.2565 3.2941 30 -0.08 0.9385 Tukey-Kramer 1.0000 0.05 -6.9840 6.4710 -13.6304 13.1175
hospbi*age_gr*sample C 6 2 C 9 2 0.3042 3.7001 30 0.08 0.9350 Tukey-Kramer 1.0000 0.05 -7.2523 7.8607 -14.7178 15.3262
hospbi*age_gr*sample C 6 2 A 9 3 -2.1428 2.3034 30 -0.93 0.3597 Tukey-Kramer 1.0000 0.05 -6.8469 2.5613 -11.4943 7.2088
hospbi*age_gr*sample C 6 2 B 9 3 -2.5065 2.3129 30 -1.08 0.2871 Tukey-Kramer 1.0000 0.05 -7.2300 2.2170 -11.8967 6.8837
hospbi*age_gr*sample C 6 2 C 9 3 -4.0324 2.3884 30 -1.69 0.1017 Tukey-Kramer 0.9904 0.05 -8.9101 0.8453 -13.7291 5.6643
hospbi*age_gr*sample A 6 3 B 6 3 -0.8082 0.4915 30 -1.64 0.1105 Tukey-Kramer 0.9930 0.05 -1.8119 0.1956 -2.8035 1.1872
hospbi*age_gr*sample A 6 3 C 6 3 -0.4022 0.4887 30 -0.82 0.4170 Tukey-Kramer 1.0000 0.05 -1.4002 0.5958 -2.3863 1.5818
hospbi*age_gr*sample A 6 3 A 9 1 -2.5481 1.5271 30 -1.67 0.1056 Tukey-Kramer 0.9917 0.05 -5.6669 0.5707 -8.7481 3.6519
hospbi*age_gr*sample A 6 3 B 9 1 -1.5061 1.5556 30 -0.97 0.3407 Tukey-Kramer 1.0000 0.05 -4.6831 1.6709 -7.8219 4.8096
hospbi*age_gr*sample A 6 3 C 9 1 -2.3923 1.7691 30 -1.35 0.1864 Tukey-Kramer 0.9995 0.05 -6.0054 1.2207 -9.5748 4.7902
hospbi*age_gr*sample A 6 3 A 9 2 0.9052 2.6046 30 0.35 0.7306 Tukey-Kramer 1.0000 0.05 -4.4142 6.2246 -9.6695 11.4800
hospbi*age_gr*sample A 6 3 B 9 2 0.9700 2.6713 30 0.36 0.7191 Tukey-Kramer 1.0000 0.05 -4.4855 6.4255 -9.8753 11.8153
hospbi*age_gr*sample A 6 3 C 9 2 1.5306 3.1583 30 0.48 0.6315 Tukey-Kramer 1.0000 0.05 -4.9195 7.9807 -11.2920 14.3532
hospbi*age_gr*sample A 6 3 A 9 3 -0.9163 1.2610 30 -0.73 0.4730 Tukey-Kramer 1.0000 0.05 -3.4916 1.6589 -6.0358 4.2031
hospbi*age_gr*sample A 6 3 B 9 3 -1.2801 1.2783 30 -1.00 0.3246 Tukey-Kramer 1.0000 0.05 -3.8907 1.3305 -6.4698 3.9097
hospbi*age_gr*sample A 6 3 C 9 3 -2.8060 1.4103 30 -1.99 0.0558 Tukey-Kramer 0.9458 0.05 -5.6861 0.07422 -8.5316 2.9197
hospbi*age_gr*sample B 6 3 C 6 3 0.4059 0.5598 30 0.73 0.4740 Tukey-Kramer 1.0000 0.05 -0.7373 1.5492 -1.8667 2.6786
hospbi*age_gr*sample B 6 3 A 9 1 -1.7400 1.5435 30 -1.13 0.2686 Tukey-Kramer 1.0000 0.05 -4.8921 1.4122 -8.0064 4.5264
hospbi*age_gr*sample B 6 3 B 9 1 -0.6980 1.5717 30 -0.44 0.6602 Tukey-Kramer 1.0000 0.05 -3.9078 2.5118 -7.0789 5.6830
hospbi*age_gr*sample B 6 3 C 9 1 -1.5842 1.7833 30 -0.89 0.3814 Tukey-Kramer 1.0000 0.05 -5.2261 2.0577 -8.8241 5.6557
hospbi*age_gr*sample B 6 3 A 9 2 1.7134 2.6143 30 0.66 0.5172 Tukey-Kramer 1.0000 0.05 -3.6257 7.0524 -8.9004 12.3272
hospbi*age_gr*sample B 6 3 B 9 2 1.7781 2.6807 30 0.66 0.5122 Tukey-Kramer 1.0000 0.05 -3.6966 7.2528 -9.1053 12.6615
hospbi*age_gr*sample B 6 3 C 9 2 2.3387 3.1663 30 0.74 0.4659 Tukey-Kramer 1.0000 0.05 -4.1276 8.8051 -10.5161 15.1936
hospbi*age_gr*sample B 6 3 A 9 3 -0.1082 1.2807 30 -0.08 0.9332 Tukey-Kramer 1.0000 0.05 -2.7238 2.5074 -5.3079 5.0915
hospbi*age_gr*sample B 6 3 B 9 3 -0.4719 1.2978 30 -0.36 0.7187 Tukey-Kramer 1.0000 0.05 -3.1223 2.1785 -5.7408 4.7970
hospbi*age_gr*sample B 6 3 C 9 3 -1.9978 1.4280 30 -1.40 0.1721 Tukey-Kramer 0.9992 0.05 -4.9141 0.9185 -7.7953 3.7997
hospbi*age_gr*sample C 6 3 A 9 1 -2.1459 1.6697 30 -1.29 0.2086 Tukey-Kramer 0.9998 0.05 -5.5559 1.2641 -8.9248 4.6330
hospbi*age_gr*sample C 6 3 B 9 1 -1.1039 1.6958 30 -0.65 0.5200 Tukey-Kramer 1.0000 0.05 -4.5672 2.3594 -7.9888 5.7810
hospbi*age_gr*sample C 6 3 C 9 1 -1.9901 1.8936 30 -1.05 0.3016 Tukey-Kramer 1.0000 0.05 -5.8573 1.8770 -9.6779 5.6976
hospbi*age_gr*sample C 6 3 A 9 2 1.3074 2.6907 30 0.49 0.6306 Tukey-Kramer 1.0000 0.05 -4.1878 6.8026 -9.6168 12.2316
hospbi*age_gr*sample C 6 3 B 9 2 1.3722 2.7553 30 0.50 0.6221 Tukey-Kramer 1.0000 0.05 -4.2549 6.9992 -9.8142 12.5585
hospbi*age_gr*sample C 6 3 C 9 2 1.9328 3.2297 30 0.60 0.5540 Tukey-Kramer 1.0000 0.05 -4.6631 8.5287 -11.1795 15.0451
hospbi*age_gr*sample C 6 3 A 9 3 -0.5141 1.4303 30 -0.36 0.7218 Tukey-Kramer 1.0000 0.05 -3.4353 2.4070 -6.3212 5.2930
hospbi*age_gr*sample C 6 3 B 9 3 -0.8779 1.4456 30 -0.61 0.5482 Tukey-Kramer 1.0000 0.05 -3.8302 2.0745 -6.7470 4.9913
hospbi*age_gr*sample C 6 3 C 9 3 -2.4038 1.5636 30 -1.54 0.1347 Tukey-Kramer 0.9971 0.05 -5.5970 0.7895 -8.7517 3.9442
hospbi*age_gr*sample A 9 1 B 9 1 1.0420 0.6502 30 1.60 0.1195 Tukey-Kramer 0.9949 0.05 -0.2858 2.3698 -1.5976 3.6816
hospbi*age_gr*sample A 9 1 C 9 1 0.1558 0.6465 30 0.24 0.8112 Tukey-Kramer 1.0000 0.05 -1.1645 1.4760 -2.4689 2.7804
hospbi*age_gr*sample A 9 1 A 9 2 3.4533 2.7240 30 1.27 0.2146 Tukey-Kramer 0.9998 0.05 -2.1098 9.0165 -7.6060 14.5126
hospbi*age_gr*sample A 9 1 B 9 2 3.5181 2.7878 30 1.26 0.2167 Tukey-Kramer 0.9998 0.05 -2.1754 9.2115 -7.8002 14.8364
hospbi*age_gr*sample A 9 1 C 9 2 4.0787 3.2574 30 1.25 0.2202 Tukey-Kramer 0.9999 0.05 -2.5739 10.7313 -9.1464 17.3038
hospbi*age_gr*sample A 9 1 A 9 3 1.6318 1.4920 30 1.09 0.2828 Tukey-Kramer 1.0000 0.05 -1.4153 4.6788 -4.4257 7.6892
hospbi*age_gr*sample A 9 1 B 9 3 1.2680 1.5067 30 0.84 0.4067 Tukey-Kramer 1.0000 0.05 -1.8090 4.3450 -4.8489 7.3850
hospbi*age_gr*sample A 9 1 C 9 3 -0.2578 1.6202 30 -0.16 0.8746 Tukey-Kramer 1.0000 0.05 -3.5666 3.0510 -6.8356 6.3199
hospbi*age_gr*sample B 9 1 C 9 1 -0.8862 0.7405 30 -1.20 0.2408 Tukey-Kramer 0.9999 0.05 -2.3986 0.6261 -3.8927 2.1203
hospbi*age_gr*sample B 9 1 A 9 2 2.4113 2.7401 30 0.88 0.3858 Tukey-Kramer 1.0000 0.05 -3.1847 8.0074 -8.7133 13.5360
hospbi*age_gr*sample B 9 1 B 9 2 2.4761 2.8035 30 0.88 0.3841 Tukey-Kramer 1.0000 0.05 -3.2495 8.2016 -8.9061 13.8582
hospbi*age_gr*sample B 9 1 C 9 2 3.0367 3.2709 30 0.93 0.3606 Tukey-Kramer 1.0000 0.05 -3.6434 9.7168 -10.2430 16.3165
hospbi*age_gr*sample B 9 1 A 9 3 0.5898 1.5212 30 0.39 0.7010 Tukey-Kramer 1.0000 0.05 -2.5169 3.6964 -5.5861 6.7657
hospbi*age_gr*sample B 9 1 B 9 3 0.2260 1.5356 30 0.15 0.8840 Tukey-Kramer 1.0000 0.05 -2.9100 3.3621 -6.0082 6.4603
hospbi*age_gr*sample B 9 1 C 9 3 -1.2998 1.6471 30 -0.79 0.4362 Tukey-Kramer 1.0000 0.05 -4.6636 2.0639 -7.9868 5.3872
hospbi*age_gr*sample C 9 1 A 9 2 3.2976 2.8667 30 1.15 0.2591 Tukey-Kramer 1.0000 0.05 -2.5570 9.1521 -8.3410 14.9362
hospbi*age_gr*sample C 9 1 B 9 2 3.3623 2.9274 30 1.15 0.2598 Tukey-Kramer 1.0000 0.05 -2.6162 9.3408 -8.5227 15.2473
hospbi*age_gr*sample C 9 1 C 9 2 3.9229 3.3777 30 1.16 0.2546 Tukey-Kramer 1.0000 0.05 -2.9752 10.8211 -9.7902 17.6361
hospbi*age_gr*sample C 9 1 A 9 3 1.4760 1.7389 30 0.85 0.4027 Tukey-Kramer 1.0000 0.05 -2.0753 5.0273 -5.5838 8.5358
hospbi*age_gr*sample C 9 1 B 9 3 1.1123 1.7515 30 0.64 0.5302 Tukey-Kramer 1.0000 0.05 -2.4647 4.6893 -5.9987 8.2232
hospbi*age_gr*sample C 9 1 C 9 3 -0.4136 1.8500 30 -0.22 0.8246 Tukey-Kramer 1.0000 0.05 -4.1919 3.3647 -7.9246 7.0974
hospbi*age_gr*sample A 9 2 B 9 2 0.06475 1.3003 30 0.05 0.9606 Tukey-Kramer 1.0000 0.05 -2.5908 2.7203 -5.2145 5.3440
hospbi*age_gr*sample A 9 2 C 9 2 0.6254 1.2929 30 0.48 0.6321 Tukey-Kramer 1.0000 0.05 -2.0152 3.2659 -4.6239 5.8747
hospbi*age_gr*sample A 9 2 A 9 3 -1.8216 2.5842 30 -0.70 0.4863 Tukey-Kramer 1.0000 0.05 -7.0992 3.4561 -12.3133 8.6702
hospbi*age_gr*sample A 9 2 B 9 3 -2.1853 2.5927 30 -0.84 0.4060 Tukey-Kramer 1.0000 0.05 -7.4803 3.1097 -12.7116 8.3410
hospbi*age_gr*sample A 9 2 C 9 3 -3.7112 2.6603 30 -1.40 0.1732 Tukey-Kramer 0.9993 0.05 -9.1442 1.7218 -14.5117 7.0894
hospbi*age_gr*sample B 9 2 C 9 2 0.5606 1.4810 30 0.38 0.7077 Tukey-Kramer 1.0000 0.05 -2.4641 3.5853 -5.4523 6.5736
hospbi*age_gr*sample B 9 2 A 9 3 -1.8863 2.6514 30 -0.71 0.4823 Tukey-Kramer 1.0000 0.05 -7.3011 3.5285 -12.6508 8.8782
hospbi*age_gr*sample B 9 2 B 9 3 -2.2500 2.6597 30 -0.85 0.4043 Tukey-Kramer 1.0000 0.05 -7.6818 3.1817 -13.0481 8.5480
hospbi*age_gr*sample B 9 2 C 9 3 -3.7759 2.7256 30 -1.39 0.1762 Tukey-Kramer 0.9993 0.05 -9.3422 1.7904 -14.8415 7.2897
hospbi*age_gr*sample C 9 2 A 9 3 -2.4469 3.1415 30 -0.78 0.4421 Tukey-Kramer 1.0000 0.05 -8.8627 3.9688 -15.2012 10.3073
hospbi*age_gr*sample C 9 2 B 9 3 -2.8107 3.1485 30 -0.89 0.3791 Tukey-Kramer 1.0000 0.05 -9.2407 3.6194 -15.5933 9.9720
hospbi*age_gr*sample C 9 2 C 9 3 -4.3366 3.2043 30 -1.35 0.1861 Tukey-Kramer 0.9995 0.05 -10.8807 2.2076 -17.3460 8.6729
hospbi*age_gr*sample A 9 3 B 9 3 -0.3637 0.4597 30 -0.79 0.4350 Tukey-Kramer 1.0000 0.05 -1.3026 0.5751 -2.2302 1.5027
hospbi*age_gr*sample A 9 3 C 9 3 -1.8896 0.4571 30 -4.13 0.0003 Tukey-Kramer 0.0421 0.05 -2.8232 -0.9560 -3.7455 -0.03371
hospbi*age_gr*sample B 9 3 C 9 3 -1.5259 0.5236 30 -2.91 0.0067 Tukey-Kramer 0.4470 0.05 -2.5953 -0.4565 -3.6518 0.6000

Data for supplemental table 2 and Figure 1

In [17]:
/*ls means values by head body and tail*/

DATA cd68_lsmeans1 (drop=age_group);
     set cd68_lsmeans;
     if age_group^="" then delete;
     stain="CD68           ";
     rename _NAME_=pancreas_region;
run;

PROC print data=cd68_lsmeans1;
run;

/*grand mean values*/

PROC means data=cd68_lsmeans1 mean;
     var lsmean;
     class hospbin;
     output out=cd68_grandmean;
run;

DATA cd68_grandmean (drop=_type_ _freq_ _stat_);
     set cd68_grandmean;
     if _stat_^="MEAN" then delete;
     if hospbin="" then delete;
     pancreas_region="Overall";
     stain="CD68           ";
run;

/*combine files into 1*/

DATA CD68_fig1;
     set CD68_lsmeans1 CD68_grandmean;
run;

PROC print data=CD68_fig1;
run;
Out[17]:
SAS Output
Obs pancreas_region hospbin LSMEAN stain
1 Head 3 2.11729 CD68
2 Head 6 2.11608 CD68
3 Head 9 3.43758 CD68
4 Body 3 2.81909 CD68
5 Body 6 2.58786 CD68
6 Body 9 3.18992 CD68
7 Tail 3 2.81956 CD68
8 Tail 6 2.41701 CD68
9 Tail 9 3.80707 CD68

The MEANS Procedure

Analysis Variable : LSMEAN
hospbin N Obs Mean
3 3 2.5853126
6 3 2.3736492
9 3 3.4781916

Obs pancreas_region hospbin LSMEAN stain
1 Head 3 2.11729 CD68
2 Head 6 2.11608 CD68
3 Head 9 3.43758 CD68
4 Body 3 2.81909 CD68
5 Body 6 2.58786 CD68
6 Body 9 3.18992 CD68
7 Tail 3 2.81956 CD68
8 Tail 6 2.41701 CD68
9 Tail 9 3.80707 CD68
10 Overall 3 2.58531 CD68
11 Overall 6 2.37365 CD68
12 Overall 9 3.47819 CD68

Insulin dataset

statistical analysis model

In [18]:
PROC glm data=insulin1;
     class hospbin age_group;
     model Head Body Tail= hospbin|age_group/nouni; 
     repeated sample_type2 / short printe; 
     lsmeans hospbin|age_group / out=insulin1_means (drop=stderr);
run;
quit;

PROC mixed data=insulin;
     class case hospbin age_group sample_type2;
     model percent_insulin=hospbin|age_group|sample_type2;
     repeated sample_type2/ subject=case(hospbin) type=un;
     lsmeans hospbin|age_group|sample_type2 /adjust=tukey cl pdiff alpha=0.05;
run;
Out[18]:
SAS Output

The GLM Procedure

Class Level Information
Class Levels Values
hospbin 3 3 6 9
age_group 3 1 2 3
Number of Observations Read 39
Number of Observations Used 39

The GLM Procedure

Repeated Measures Analysis of Variance

Repeated Measures Level Information
Dependent Variable Head Body Tail
Level of sample_type2 1 2 3
Partial Correlation Coefficients from the Error SSCP Matrix / Prob > |r|
DF = 30 Head Body Tail
Head
1.000000
 
0.949948
<.0001
0.881226
<.0001
Body
0.949948
<.0001
1.000000
 
0.939152
<.0001
Tail
0.881226
<.0001
0.939152
<.0001
1.000000
 
E = Error SSCP Matrix

sample_type2_N represents the contrast between the nth level of sample_type2 and the last
  sample_type2_1 sample_type2_2
sample_type2_1 45.188 18.763
sample_type2_2 18.763 18.114
Partial Correlation Coefficients from the Error SSCP Matrix of the Variables Defined by the Specified Transformation / Prob > |r|
DF = 30 sample_type2_1 sample_type2_2
sample_type2_1
1.000000
 
0.655805
<.0001
sample_type2_2
0.655805
<.0001
1.000000
 
Sphericity Tests
Variables DF Mauchly's Criterion Chi-Square Pr > ChiSq
Transformed Variates 2 0.465673 22.163876 <.0001
Orthogonal Components 2 0.7054901 10.117014 0.0064
MANOVA Test Criteria and Exact F Statistics for the Hypothesis of no sample_type2 Effect
H = Type III SSCP Matrix for sample_type2
E = Error SSCP Matrix

S=1 M=0 N=13.5
Statistic Value F Value Num DF Den DF Pr > F
Wilks' Lambda 0.52375843 13.18 2 29 <.0001
Pillai's Trace 0.47624157 13.18 2 29 <.0001
Hotelling-Lawley Trace 0.90927713 13.18 2 29 <.0001
Roy's Greatest Root 0.90927713 13.18 2 29 <.0001
MANOVA Test Criteria and F Approximations for the Hypothesis of no sample_type2*hospbin Effect
H = Type III SSCP Matrix for sample_type2*hospbin
E = Error SSCP Matrix

S=2 M=-0.5 N=13.5
Statistic Value F Value Num DF Den DF Pr > F
NOTE: F Statistic for Roy's Greatest Root is an upper bound.
NOTE: F Statistic for Wilks' Lambda is exact.
Wilks' Lambda 0.91606221 0.65 4 58 0.6293
Pillai's Trace 0.08552742 0.67 4 60 0.6153
Hotelling-Lawley Trace 0.08989364 0.64 4 33.787 0.6343
Roy's Greatest Root 0.06182692 0.93 2 30 0.4066
MANOVA Test Criteria and F Approximations for the Hypothesis of no sample_type2*age_group Effect
H = Type III SSCP Matrix for sample_type2*age_group
E = Error SSCP Matrix

S=2 M=-0.5 N=13.5
Statistic Value F Value Num DF Den DF Pr > F
NOTE: F Statistic for Roy's Greatest Root is an upper bound.
NOTE: F Statistic for Wilks' Lambda is exact.
Wilks' Lambda 0.73333544 2.43 4 58 0.0575
Pillai's Trace 0.26679863 2.31 4 60 0.0682
Hotelling-Lawley Trace 0.36344961 2.61 4 33.787 0.0529
Roy's Greatest Root 0.36294587 5.44 2 30 0.0096
MANOVA Test Criteria and F Approximations for the Hypothesis of no sample_type2*hospbin*age_group Effect
H = Type III SSCP Matrix for sample_type2*hospbin*age_group
E = Error SSCP Matrix

S=2 M=0.5 N=13.5
Statistic Value F Value Num DF Den DF Pr > F
NOTE: F Statistic for Roy's Greatest Root is an upper bound.
NOTE: F Statistic for Wilks' Lambda is exact.
Wilks' Lambda 0.77474650 0.99 8 58 0.4558
Pillai's Trace 0.22961082 0.97 8 60 0.4659
Hotelling-Lawley Trace 0.28512058 1.01 8 39.176 0.4416
Roy's Greatest Root 0.26380073 1.98 4 30 0.1233

The GLM Procedure

Repeated Measures Analysis of Variance

Tests of Hypotheses for Between Subjects Effects

Source DF Type III SS Mean Square F Value Pr > F
hospbin 2 14.4592667 7.2296333 0.49 0.6193
age_group 2 261.7807267 130.8903633 8.81 0.0010
hospbin*age_group 4 70.2225689 17.5556422 1.18 0.3386
Error 30 445.4928129 14.8497604    

The GLM Procedure

Repeated Measures Analysis of Variance

Univariate Tests of Hypotheses for Within Subject Effects

Source DF Type III SS Mean Square F Value Pr > F Adj Pr > F
G - G H-F-L
sample_type2 2 6.54906638 3.27453319 6.62 0.0025 0.0057 0.0051
sample_type2*hospbin 4 1.58133910 0.39533478 0.80 0.5307 0.5041 0.5085
sample_type2*age_group 4 4.73081484 1.18270371 2.39 0.0607 0.0791 0.0760
sample_type2*hospbin*age_group 8 3.46848879 0.43356110 0.88 0.5417 0.5222 0.5255
Error(sample_type2) 60 29.69284008 0.49488067        
Greenhouse-Geisser Epsilon 0.7725
Huynh-Feldt-Lecoutre Epsilon 0.8064

The GLM Procedure

Least Squares Means

hospbin Head LSMEAN
3 3.67605328
6 2.59538527
9 2.25901072
Plot of Head least-squares means for hospbin.
hospbin Body LSMEAN
3 2.97310362
6 2.22844238
9 2.07232736
Plot of Body least-squares means for hospbin.
hospbin Tail LSMEAN
3 3.54317333
6 3.19100765
9 2.69676590
Plot of Tail least-squares means for hospbin.
age_group Head LSMEAN
1 5.29526769
2 2.00287461
3 1.23230698
Plot of Head least-squares means for age_group.
age_group Body LSMEAN
1 4.27700002
2 1.70135672
3 1.29551662
Plot of Body least-squares means for age_group.
age_group Tail LSMEAN
1 5.14813111
2 2.36051844
3 1.92229733
Plot of Tail least-squares means for age_group.
hospbin age_group Head LSMEAN
3 1 8.15237222
3 2 1.57745333
3 3 1.29833429
6 1 4.95603750
6 2 1.65544717
6 3 1.17467114
9 1 2.77739333
9 2 2.77572333
9 3 1.22391550
Plot of Head least-squares means for hospbin*age_group.
hospbin age_group Body LSMEAN
3 1 6.01730289
3 2 1.51584667
3 3 1.38616129
6 1 4.23163383
6 2 1.13735350
6 3 1.31633981
9 1 2.58206333
9 2 2.45087000
9 3 1.18404875
Plot of Body least-squares means for hospbin*age_group.
hospbin age_group Tail LSMEAN
3 1 6.90823000
3 2 1.92138000
3 3 1.79991000
6 1 5.24763333
6 2 2.33609867
6 3 1.98929095
9 1 3.28853000
9 2 2.82407667
9 3 1.97769104
Plot of Tail least-squares means for hospbin*age_group.

The Mixed Procedure

Model Information
Data Set WORK.INSULIN
Dependent Variable percent_insulin
Covariance Structure Unstructured
Subject Effect Case(hospbin)
Estimation Method REML
Residual Variance Method None
Fixed Effects SE Method Model-Based
Degrees of Freedom Method Between-Within
Class Level Information
Class Levels Values
Case 39 6003 6005 6007 6008 6011 6019 6047 6048 6057 6060 6073 6099 6104 6106 6115 6117 6126 6129 6131 6134 6140 6144 6162 6165 6172 6174 6178 6179 6187 6200 6219 6229 6230 6235 6250 6251 6254 6278 6279
hospbin 3 3 6 9
age_group 3 1 2 3
sample_type2 3 A B C
Dimensions
Covariance Parameters 6
Columns in X 64
Columns in Z 0
Subjects 39
Max Obs per Subject 3
Number of Observations
Number of Observations Read 117
Number of Observations Used 117
Number of Observations Not Used 0
Iteration History
Iteration Evaluations -2 Res Log Like Criterion
0 1 439.24643330  
1 1 303.07256043 0.00000000
Convergence criteria met.
Covariance Parameter Estimates
Cov Parm Subject Estimate
UN(1,1) Case(hospbin) 6.7337
UN(2,1) Case(hospbin) 4.9685
UN(2,2) Case(hospbin) 4.0626
UN(3,1) Case(hospbin) 5.1353
UN(3,2) Case(hospbin) 4.2510
UN(3,3) Case(hospbin) 5.0433
Fit Statistics
-2 Res Log Likelihood 303.1
AIC (Smaller is Better) 315.1
AICC (Smaller is Better) 316.1
BIC (Smaller is Better) 325.1
Null Model Likelihood Ratio Test
DF Chi-Square Pr > ChiSq
5 136.17 <.0001
Type 3 Tests of Fixed Effects
Effect Num DF Den DF F Value Pr > F
hospbin 2 30 0.49 0.6193
age_group 2 30 8.81 0.0010
hospbin*age_group 4 30 1.18 0.3386
sample_type2 2 30 13.64 <.0001
hospbin*sample_type2 4 30 0.67 0.6151
age_group*sample_typ 4 30 2.73 0.0478
hospbi*age_gr*sample 8 30 1.07 0.4101
Least Squares Means
Effect sample_type2 hospbin age_group Estimate Standard
Error
DF t Value Pr > |t| Alpha Lower Upper
hospbin   3   3.3974 0.7260 30 4.68 <.0001 0.05 1.9148 4.8801
hospbin   6   2.6716 0.7008 30 3.81 0.0006 0.05 1.2405 4.1028
hospbin   9   2.3427 0.8696 30 2.69 0.0115 0.05 0.5667 4.1187
age_group     1 4.9068 0.6770 30 7.25 <.0001 0.05 3.5242 6.2894
age_group     2 2.0216 1.0488 30 1.93 0.0634 0.05 -0.1204 4.1635
age_group     3 1.4834 0.4648 30 3.19 0.0033 0.05 0.5341 2.4327
hospbin*age_group   3 1 7.0260 1.2845 30 5.47 <.0001 0.05 4.4026 9.6493
hospbin*age_group   3 2 1.6716 1.5732 30 1.06 0.2965 0.05 -1.5413 4.8845
hospbin*age_group   3 3 1.4948 0.7866 30 1.90 0.0670 0.05 -0.1117 3.1013
hospbin*age_group   6 1 4.8118 1.1124 30 4.33 0.0002 0.05 2.5399 7.0836
hospbin*age_group   6 2 1.7096 1.5732 30 1.09 0.2858 0.05 -1.5033 4.9225
hospbin*age_group   6 3 1.4934 0.8409 30 1.78 0.0859 0.05 -0.2239 3.2108
hospbin*age_group   9 1 2.8827 1.1124 30 2.59 0.0146 0.05 0.6108 5.1545
hospbin*age_group   9 2 2.6836 2.2248 30 1.21 0.2372 0.05 -1.8602 7.2273
hospbin*age_group   9 3 1.4619 0.7866 30 1.86 0.0729 0.05 -0.1446 3.0683
sample_type2 A     2.8435 0.5179 30 5.49 <.0001 0.05 1.7858 3.9011
sample_type2 B     2.4246 0.4023 30 6.03 <.0001 0.05 1.6031 3.2461
sample_type2 C     3.1436 0.4482 30 7.01 <.0001 0.05 2.2283 4.0590
hospbin*sample_type2 A 3   3.6761 0.8468 30 4.34 0.0001 0.05 1.9467 5.4054
hospbin*sample_type2 B 3   2.9731 0.6577 30 4.52 <.0001 0.05 1.6299 4.3163
hospbin*sample_type2 C 3   3.5432 0.7328 30 4.84 <.0001 0.05 2.0466 5.0398
hospbin*sample_type2 A 6   2.5954 0.8173 30 3.18 0.0034 0.05 0.9262 4.2646
hospbin*sample_type2 B 6   2.2284 0.6348 30 3.51 0.0014 0.05 0.9319 3.5250
hospbin*sample_type2 C 6   3.1910 0.7073 30 4.51 <.0001 0.05 1.7464 4.6356
hospbin*sample_type2 A 9   2.2590 1.0143 30 2.23 0.0336 0.05 0.1876 4.3304
hospbin*sample_type2 B 9   2.0723 0.7878 30 2.63 0.0133 0.05 0.4634 3.6813
hospbin*sample_type2 C 9   2.6968 0.8778 30 3.07 0.0045 0.05 0.9041 4.4894
age_group*sample_typ A   1 5.2953 0.7896 30 6.71 <.0001 0.05 3.6827 6.9079
age_group*sample_typ B   1 4.2770 0.6133 30 6.97 <.0001 0.05 3.0244 5.5296
age_group*sample_typ C   1 5.1481 0.6834 30 7.53 <.0001 0.05 3.7525 6.5437
age_group*sample_typ A   2 2.0029 1.2233 30 1.64 0.1120 0.05 -0.4954 4.5011
age_group*sample_typ B   2 1.7014 0.9502 30 1.79 0.0835 0.05 -0.2391 3.6418
age_group*sample_typ C   2 2.3605 1.0586 30 2.23 0.0334 0.05 0.1985 4.5226
age_group*sample_typ A   3 1.2323 0.5422 30 2.27 0.0304 0.05 0.1251 2.3395
age_group*sample_typ B   3 1.2955 0.4211 30 3.08 0.0044 0.05 0.4355 2.1555
age_group*sample_typ C   3 1.9223 0.4692 30 4.10 0.0003 0.05 0.9641 2.8805
hospbi*age_gr*sample A 3 1 8.1524 1.4982 30 5.44 <.0001 0.05 5.0927 11.2121
hospbi*age_gr*sample B 3 1 6.0173 1.1637 30 5.17 <.0001 0.05 3.6407 8.3939
hospbi*age_gr*sample C 3 1 6.9082 1.2966 30 5.33 <.0001 0.05 4.2603 9.5562
hospbi*age_gr*sample A 3 2 1.5775 1.8349 30 0.86 0.3968 0.05 -2.1699 5.3248
hospbi*age_gr*sample B 3 2 1.5158 1.4252 30 1.06 0.2960 0.05 -1.3949 4.4266
hospbi*age_gr*sample C 3 2 1.9214 1.5880 30 1.21 0.2357 0.05 -1.3217 5.1644
hospbi*age_gr*sample A 3 3 1.2983 0.9174 30 1.42 0.1673 0.05 -0.5753 3.1720
hospbi*age_gr*sample B 3 3 1.3862 0.7126 30 1.95 0.0612 0.05 -0.06919 2.8415
hospbi*age_gr*sample C 3 3 1.7999 0.7940 30 2.27 0.0308 0.05 0.1784 3.4214
hospbi*age_gr*sample A 6 1 4.9560 1.2975 30 3.82 0.0006 0.05 2.3063 7.6058
hospbi*age_gr*sample B 6 1 4.2316 1.0078 30 4.20 0.0002 0.05 2.1734 6.2898
hospbi*age_gr*sample C 6 1 5.2476 1.1229 30 4.67 <.0001 0.05 2.9544 7.5408
hospbi*age_gr*sample A 6 2 1.6554 1.8349 30 0.90 0.3741 0.05 -2.0919 5.4028
hospbi*age_gr*sample B 6 2 1.1374 1.4252 30 0.80 0.4311 0.05 -1.7734 4.0481
hospbi*age_gr*sample C 6 2 2.3361 1.5880 30 1.47 0.1517 0.05 -0.9070 5.5792
hospbi*age_gr*sample A 6 3 1.1747 0.9808 30 1.20 0.2404 0.05 -0.8284 3.1777
hospbi*age_gr*sample B 6 3 1.3163 0.7618 30 1.73 0.0943 0.05 -0.2395 2.8722
hospbi*age_gr*sample C 6 3 1.9893 0.8488 30 2.34 0.0259 0.05 0.2558 3.7228
hospbi*age_gr*sample A 9 1 2.7774 1.2975 30 2.14 0.0406 0.05 0.1276 5.4272
hospbi*age_gr*sample B 9 1 2.5821 1.0078 30 2.56 0.0157 0.05 0.5239 4.6402
hospbi*age_gr*sample C 9 1 3.2885 1.1229 30 2.93 0.0064 0.05 0.9953 5.5817
hospbi*age_gr*sample A 9 2 2.7757 2.5949 30 1.07 0.2933 0.05 -2.5238 8.0753
hospbi*age_gr*sample B 9 2 2.4509 2.0156 30 1.22 0.2335 0.05 -1.6655 6.5672
hospbi*age_gr*sample C 9 2 2.8241 2.2457 30 1.26 0.2183 0.05 -1.7623 7.4105
hospbi*age_gr*sample A 9 3 1.2239 0.9174 30 1.33 0.1922 0.05 -0.6498 3.0976
hospbi*age_gr*sample B 9 3 1.1840 0.7126 30 1.66 0.1070 0.05 -0.2713 2.6394
hospbi*age_gr*sample C 9 3 1.9777 0.7940 30 2.49 0.0185 0.05 0.3562 3.5992
Differences of Least Squares Means
Effect sample_type2 hospbin age_group _sample_type2 hospbin _age_group Estimate Standard
Error
DF t Value Pr > |t| Adjustment Adj P Alpha Lower Upper Adj Lower Adj Upper
hospbin   3     6   0.7258 1.0090 30 0.72 0.4775 Tukey-Kramer 0.7541 0.05 -1.3349 2.7865 -1.7617 3.2133
hospbin   3     9   1.0547 1.1328 30 0.93 0.3593 Tukey-Kramer 0.6252 0.05 -1.2588 3.3683 -1.7380 3.8475
hospbin   6     9   0.3289 1.1168 30 0.29 0.7704 Tukey-Kramer 0.9534 0.05 -1.9520 2.6098 -2.4244 3.0822
age_group     1     2 2.8852 1.2483 30 2.31 0.0279 Tukey-Kramer 0.0695 0.05 0.3358 5.4346 -0.1922 5.9626
age_group     1     3 3.4234 0.8212 30 4.17 0.0002 Tukey-Kramer 0.0007 0.05 1.7463 5.1006 1.3989 5.4479
age_group     2     3 0.5382 1.1472 30 0.47 0.6424 Tukey-Kramer 0.8862 0.05 -1.8047 2.8811 -2.2899 3.3663
hospbin*age_group   3 1   3 2 5.3544 2.0310 30 2.64 0.0131 Tukey-Kramer 0.2140 0.05 1.2066 9.5022 -1.4240 12.1328
hospbin*age_group   3 1   3 3 5.5312 1.5062 30 3.67 0.0009 Tukey-Kramer 0.0226 0.05 2.4550 8.6073 0.5041 10.5582
hospbin*age_group   3 1   6 1 2.2142 1.6993 30 1.30 0.2025 Tukey-Kramer 0.9226 0.05 -1.2561 5.6845 -3.4571 7.8855
hospbin*age_group   3 1   6 2 5.3163 2.0310 30 2.62 0.0137 Tukey-Kramer 0.2213 0.05 1.1685 9.4642 -1.4621 12.0948
hospbin*age_group   3 1   6 3 5.5325 1.5353 30 3.60 0.0011 Tukey-Kramer 0.0267 0.05 2.3971 8.6680 0.4085 10.6566
hospbin*age_group   3 1   9 1 4.1433 1.6993 30 2.44 0.0209 Tukey-Kramer 0.3009 0.05 0.6730 7.6136 -1.5279 9.8146
hospbin*age_group   3 1   9 2 4.3424 2.5690 30 1.69 0.1013 Tukey-Kramer 0.7474 0.05 -0.9042 9.5891 -4.2317 12.9165
hospbin*age_group   3 1   9 3 5.5641 1.5062 30 3.69 0.0009 Tukey-Kramer 0.0214 0.05 2.4880 8.6402 0.5371 10.5911
hospbin*age_group   3 2   3 3 0.1768 1.7589 30 0.10 0.9206 Tukey-Kramer 1.0000 0.05 -3.4154 3.7689 -5.6935 6.0471
hospbin*age_group   3 2   6 1 -3.1402 1.9268 30 -1.63 0.1136 Tukey-Kramer 0.7814 0.05 -7.0752 0.7948 -9.5708 3.2904
hospbin*age_group   3 2   6 2 -0.03807 2.2248 30 -0.02 0.9865 Tukey-Kramer 1.0000 0.05 -4.5818 4.5057 -7.4635 7.3873
hospbin*age_group   3 2   6 3 0.1781 1.7838 30 0.10 0.9211 Tukey-Kramer 1.0000 0.05 -3.4650 3.8212 -5.7754 6.1317
hospbin*age_group   3 2   9 1 -1.2111 1.9268 30 -0.63 0.5344 Tukey-Kramer 0.9993 0.05 -5.1461 2.7239 -7.6417 5.2195
hospbin*age_group   3 2   9 2 -1.0120 2.7249 30 -0.37 0.7130 Tukey-Kramer 1.0000 0.05 -6.5769 4.5529 -10.1062 8.0822
hospbin*age_group   3 2   9 3 0.2097 1.7589 30 0.12 0.9059 Tukey-Kramer 1.0000 0.05 -3.3825 3.8018 -5.6606 6.0800
hospbin*age_group   3 3   6 1 -3.3170 1.3624 30 -2.43 0.0211 Tukey-Kramer 0.3027 0.05 -6.0994 -0.5345 -7.8641 1.2301
hospbin*age_group   3 3   6 2 -0.2148 1.7589 30 -0.12 0.9036 Tukey-Kramer 1.0000 0.05 -3.8070 3.3773 -6.0851 5.6555
hospbin*age_group   3 3   6 3 0.001368 1.1515 30 0.00 0.9991 Tukey-Kramer 1.0000 0.05 -2.3502 2.3530 -3.8416 3.8444
hospbin*age_group   3 3   9 1 -1.3879 1.3624 30 -1.02 0.3165 Tukey-Kramer 0.9809 0.05 -4.1703 1.3946 -5.9350 3.1593
hospbin*age_group   3 3   9 2 -1.1888 2.3598 30 -0.50 0.6181 Tukey-Kramer 0.9999 0.05 -6.0081 3.6306 -9.0646 6.6871
hospbin*age_group   3 3   9 3 0.03292 1.1124 30 0.03 0.9766 Tukey-Kramer 1.0000 0.05 -2.2389 2.3048 -3.6798 3.7456
hospbin*age_group   6 1   6 2 3.1021 1.9268 30 1.61 0.1179 Tukey-Kramer 0.7920 0.05 -0.8329 7.0371 -3.3285 9.5327
hospbin*age_group   6 1   6 3 3.3183 1.3945 30 2.38 0.0239 Tukey-Kramer 0.3305 0.05 0.4704 6.1663 -1.3358 7.9725
hospbin*age_group   6 1   9 1 1.9291 1.5732 30 1.23 0.2297 Tukey-Kramer 0.9440 0.05 -1.2838 5.1420 -3.3215 7.1797
hospbin*age_group   6 1   9 2 2.1282 2.4874 30 0.86 0.3990 Tukey-Kramer 0.9937 0.05 -2.9518 7.2083 -6.1736 10.4301
hospbin*age_group   6 1   9 3 3.3499 1.3624 30 2.46 0.0199 Tukey-Kramer 0.2910 0.05 0.5674 6.1323 -1.1972 7.8970
hospbin*age_group   6 2   6 3 0.2162 1.7838 30 0.12 0.9043 Tukey-Kramer 1.0000 0.05 -3.4269 3.8593 -5.7374 6.1698
hospbin*age_group   6 2   9 1 -1.1730 1.9268 30 -0.61 0.5472 Tukey-Kramer 0.9994 0.05 -5.1080 2.7620 -7.6036 5.2576
hospbin*age_group   6 2   9 2 -0.9739 2.7249 30 -0.36 0.7233 Tukey-Kramer 1.0000 0.05 -6.5388 4.5910 -10.0682 8.1203
hospbin*age_group   6 2   9 3 0.2477 1.7589 30 0.14 0.8889 Tukey-Kramer 1.0000 0.05 -3.3444 3.8399 -5.6226 6.1180
hospbin*age_group   6 3   9 1 -1.3892 1.3945 30 -1.00 0.3271 Tukey-Kramer 0.9834 0.05 -4.2372 1.4587 -6.0434 3.2649
hospbin*age_group   6 3   9 2 -1.1901 2.3785 30 -0.50 0.6205 Tukey-Kramer 0.9999 0.05 -6.0476 3.6673 -9.1282 6.7480
hospbin*age_group   6 3   9 3 0.03155 1.1515 30 0.03 0.9783 Tukey-Kramer 1.0000 0.05 -2.3201 2.3832 -3.8115 3.8746
hospbin*age_group   9 1   9 2 0.1991 2.4874 30 0.08 0.9367 Tukey-Kramer 1.0000 0.05 -4.8809 5.2792 -8.1028 8.5010
hospbin*age_group   9 1   9 3 1.4208 1.3624 30 1.04 0.3054 Tukey-Kramer 0.9780 0.05 -1.3617 4.2032 -3.1263 5.9679
hospbin*age_group   9 2   9 3 1.2217 2.3598 30 0.52 0.6085 Tukey-Kramer 0.9998 0.05 -3.5977 6.0410 -6.6542 9.0975
sample_type2 A     B     0.4189 0.1850 30 2.26 0.0310 Tukey-Kramer 0.0767 0.05 0.04105 0.7967 -0.03719 0.8749
sample_type2 A     C     -0.3002 0.2449 30 -1.23 0.2299 Tukey-Kramer 0.4478 0.05 -0.8004 0.2001 -0.9040 0.3037
sample_type2 B     C     -0.7190 0.1551 30 -4.64 <.0001 Tukey-Kramer 0.0002 0.05 -1.0357 -0.4023 -1.1013 -0.3367
hospbin*sample_type2 A 3   B 3   0.7029 0.3025 30 2.32 0.0271 Tukey-Kramer 0.3601 0.05 0.08521 1.3207 -0.3066 1.7125
hospbin*sample_type2 A 3   C 3   0.1329 0.4005 30 0.33 0.7423 Tukey-Kramer 1.0000 0.05 -0.6850 0.9508 -1.2037 1.4695
hospbin*sample_type2 A 3   A 6   1.0807 1.1769 30 0.92 0.3658 Tukey-Kramer 0.9901 0.05 -1.3228 3.4842 -2.8472 5.0085
hospbin*sample_type2 A 3   B 6   1.4476 1.0583 30 1.37 0.1815 Tukey-Kramer 0.9010 0.05 -0.7138 3.6090 -2.0845 4.9798
hospbin*sample_type2 A 3   C 6   0.4850 1.1033 30 0.44 0.6634 Tukey-Kramer 0.9999 0.05 -1.7683 2.7383 -3.1973 4.1674
hospbin*sample_type2 A 3   A 9   1.4170 1.3213 30 1.07 0.2921 Tukey-Kramer 0.9740 0.05 -1.2814 4.1154 -2.9927 5.8268
hospbin*sample_type2 A 3   B 9   1.6037 1.1566 30 1.39 0.1758 Tukey-Kramer 0.8942 0.05 -0.7583 3.9658 -2.2564 5.4638
hospbin*sample_type2 A 3   C 9   0.9793 1.2196 30 0.80 0.4283 Tukey-Kramer 0.9959 0.05 -1.5115 3.4701 -3.0912 5.0498
hospbin*sample_type2 B 3   C 3   -0.5701 0.2536 30 -2.25 0.0321 Tukey-Kramer 0.4026 0.05 -1.0879 -0.05222 -1.4163 0.2762
hospbin*sample_type2 B 3   A 6   0.3777 1.0491 30 0.36 0.7213 Tukey-Kramer 1.0000 0.05 -1.7648 2.5203 -3.1237 3.8791
hospbin*sample_type2 B 3   B 6   0.7447 0.9141 30 0.81 0.4217 Tukey-Kramer 0.9955 0.05 -1.1222 2.6116 -2.3062 3.7955
hospbin*sample_type2 B 3   C 6   -0.2179 0.9659 30 -0.23 0.8230 Tukey-Kramer 1.0000 0.05 -2.1905 1.7547 -3.4415 3.0057
hospbin*sample_type2 B 3   A 9   0.7141 1.2089 30 0.59 0.5591 Tukey-Kramer 0.9995 0.05 -1.7547 3.1829 -3.3205 4.7487
hospbin*sample_type2 B 3   B 9   0.9008 1.0263 30 0.88 0.3871 Tukey-Kramer 0.9926 0.05 -1.1952 2.9967 -2.5244 4.3260
hospbin*sample_type2 B 3   C 9   0.2763 1.0969 30 0.25 0.8028 Tukey-Kramer 1.0000 0.05 -1.9637 2.5164 -3.3844 3.9371
hospbin*sample_type2 C 3   A 6   0.9478 1.0977 30 0.86 0.3948 Tukey-Kramer 0.9934 0.05 -1.2941 3.1897 -2.7159 4.6115
hospbin*sample_type2 C 3   B 6   1.3147 0.9696 30 1.36 0.1852 Tukey-Kramer 0.9052 0.05 -0.6654 3.2948 -1.9212 4.5506
hospbin*sample_type2 C 3   C 6   0.3522 1.0185 30 0.35 0.7319 Tukey-Kramer 1.0000 0.05 -1.7279 2.4322 -3.0471 3.7514
hospbin*sample_type2 C 3   A 9   1.2842 1.2513 30 1.03 0.3130 Tukey-Kramer 0.9800 0.05 -1.2713 3.8397 -2.8921 5.4604
hospbin*sample_type2 C 3   B 9   1.4708 1.0760 30 1.37 0.1818 Tukey-Kramer 0.9013 0.05 -0.7266 3.6682 -2.1202 5.0619
hospbin*sample_type2 C 3   C 9   0.8464 1.1435 30 0.74 0.4649 Tukey-Kramer 0.9977 0.05 -1.4889 3.1817 -2.9699 4.6627
hospbin*sample_type2 A 6   B 6   0.3669 0.2920 30 1.26 0.2185 Tukey-Kramer 0.9360 0.05 -0.2293 0.9632 -0.6075 1.3414
hospbin*sample_type2 A 6   C 6   -0.5956 0.3866 30 -1.54 0.1338 Tukey-Kramer 0.8274 0.05 -1.3851 0.1938 -1.8858 0.6945
hospbin*sample_type2 A 6   A 9   0.3364 1.3026 30 0.26 0.7980 Tukey-Kramer 1.0000 0.05 -2.3239 2.9966 -4.0111 4.6838
hospbin*sample_type2 A 6   B 9   0.5231 1.1352 30 0.46 0.6483 Tukey-Kramer 0.9999 0.05 -1.7953 2.8415 -3.2657 4.3118
hospbin*sample_type2 A 6   C 9   -0.1014 1.1994 30 -0.08 0.9332 Tukey-Kramer 1.0000 0.05 -2.5509 2.3481 -4.1043 3.9016
hospbin*sample_type2 B 6   C 6   -0.9626 0.2447 30 -3.93 0.0005 Tukey-Kramer 0.0118 0.05 -1.4624 -0.4627 -1.7794 -0.1457
hospbin*sample_type2 B 6   A 9   -0.03057 1.1966 30 -0.03 0.9798 Tukey-Kramer 1.0000 0.05 -2.4743 2.4132 -4.0241 3.9630
hospbin*sample_type2 B 6   B 9   0.1561 1.0118 30 0.15 0.8784 Tukey-Kramer 1.0000 0.05 -1.9102 2.2225 -3.2207 3.5329
hospbin*sample_type2 B 6   C 9   -0.4683 1.0833 30 -0.43 0.6686 Tukey-Kramer 1.0000 0.05 -2.6807 1.7441 -4.0838 3.1472
hospbin*sample_type2 C 6   A 9   0.9320 1.2366 30 0.75 0.4569 Tukey-Kramer 0.9974 0.05 -1.5934 3.4574 -3.1950 5.0590
hospbin*sample_type2 C 6   B 9   1.1187 1.0588 30 1.06 0.2991 Tukey-Kramer 0.9762 0.05 -1.0436 3.2810 -2.4150 4.6523
hospbin*sample_type2 C 6   C 9   0.4942 1.1273 30 0.44 0.6642 Tukey-Kramer 0.9999 0.05 -1.8080 2.7965 -3.2682 4.2566
hospbin*sample_type2 A 9   B 9   0.1867 0.3623 30 0.52 0.6101 Tukey-Kramer 0.9998 0.05 -0.5533 0.9266 -1.0225 1.3959
hospbin*sample_type2 A 9   C 9   -0.4378 0.4797 30 -0.91 0.3688 Tukey-Kramer 0.9905 0.05 -1.4175 0.5419 -2.0388 1.1633
hospbin*sample_type2 B 9   C 9   -0.6244 0.3037 30 -2.06 0.0486 Tukey-Kramer 0.5195 0.05 -1.2447 -0.00415 -1.6381 0.3892
age_group*sample_typ A   1 B   1 1.0183 0.2821 30 3.61 0.0011 Tukey-Kramer 0.0263 0.05 0.4422 1.5943 0.07690 1.9596
age_group*sample_typ A   1 C   1 0.1471 0.3735 30 0.39 0.6964 Tukey-Kramer 1.0000 0.05 -0.6156 0.9098 -1.0993 1.3935
age_group*sample_typ A   1 A   2 3.2924 1.4560 30 2.26 0.0312 Tukey-Kramer 0.3951 0.05 0.3189 6.2659 -1.5669 8.1517
age_group*sample_typ A   1 B   2 3.5939 1.2354 30 2.91 0.0068 Tukey-Kramer 0.1266 0.05 1.0708 6.1170 -0.5293 7.7172
age_group*sample_typ A   1 C   2 2.9347 1.3207 30 2.22 0.0340 Tukey-Kramer 0.4178 0.05 0.2375 5.6320 -1.4730 7.3425
age_group*sample_typ A   1 A   3 4.0630 0.9578 30 4.24 0.0002 Tukey-Kramer 0.0053 0.05 2.1068 6.0191 0.8662 7.2597
age_group*sample_typ A   1 B   3 3.9998 0.8949 30 4.47 0.0001 Tukey-Kramer 0.0029 0.05 2.1721 5.8274 1.0131 6.9864
age_group*sample_typ A   1 C   3 3.3730 0.9185 30 3.67 0.0009 Tukey-Kramer 0.0226 0.05 1.4972 5.2488 0.3075 6.4384
age_group*sample_typ B   1 C   1 -0.8711 0.2364 30 -3.68 0.0009 Tukey-Kramer 0.0219 0.05 -1.3540 -0.3882 -1.6603 -0.08198
age_group*sample_typ B   1 A   2 2.2741 1.3684 30 1.66 0.1070 Tukey-Kramer 0.7636 0.05 -0.5205 5.0688 -2.2929 6.8412
age_group*sample_typ B   1 B   2 2.5756 1.1309 30 2.28 0.0301 Tukey-Kramer 0.3859 0.05 0.2660 4.8853 -1.1988 6.3501
age_group*sample_typ B   1 C   2 1.9165 1.2235 30 1.57 0.1277 Tukey-Kramer 0.8147 0.05 -0.5822 4.4152 -2.1669 5.9998
age_group*sample_typ B   1 A   3 3.0447 0.8186 30 3.72 0.0008 Tukey-Kramer 0.0201 0.05 1.3729 4.7165 0.3126 5.7767
age_group*sample_typ B   1 B   3 2.9815 0.7440 30 4.01 0.0004 Tukey-Kramer 0.0097 0.05 1.4621 4.5009 0.4985 5.4645
age_group*sample_typ B   1 C   3 2.3547 0.7722 30 3.05 0.0048 Tukey-Kramer 0.0946 0.05 0.7776 3.9318 -0.2225 4.9320
age_group*sample_typ C   1 A   2 3.1453 1.4012 30 2.24 0.0323 Tukey-Kramer 0.4047 0.05 0.2836 6.0069 -1.5312 7.8217
age_group*sample_typ C   1 B   2 3.4468 1.1704 30 2.95 0.0062 Tukey-Kramer 0.1177 0.05 1.0566 5.8370 -0.4593 7.3529
age_group*sample_typ C   1 C   2 2.7876 1.2600 30 2.21 0.0347 Tukey-Kramer 0.4236 0.05 0.2143 5.3610 -1.4178 6.9930
age_group*sample_typ C   1 A   3 3.9158 0.8723 30 4.49 <.0001 Tukey-Kramer 0.0028 0.05 2.1344 5.6973 1.0045 6.8271
age_group*sample_typ C   1 B   3 3.8526 0.8027 30 4.80 <.0001 Tukey-Kramer 0.0012 0.05 2.2133 5.4919 1.1737 6.5316
age_group*sample_typ C   1 C   3 3.2258 0.8289 30 3.89 0.0005 Tukey-Kramer 0.0131 0.05 1.5329 4.9187 0.4593 5.9924
age_group*sample_typ A   2 B   2 0.3015 0.4370 30 0.69 0.4955 Tukey-Kramer 0.9986 0.05 -0.5909 1.1939 -1.1568 1.7599
age_group*sample_typ A   2 C   2 -0.3576 0.5786 30 -0.62 0.5411 Tukey-Kramer 0.9994 0.05 -1.5392 0.8239 -2.2886 1.5733
age_group*sample_typ A   2 A   3 0.7706 1.3380 30 0.58 0.5690 Tukey-Kramer 0.9996 0.05 -1.9620 3.5032 -3.6951 5.2362
age_group*sample_typ A   2 B   3 0.7074 1.2937 30 0.55 0.5886 Tukey-Kramer 0.9997 0.05 -1.9348 3.3495 -3.6104 5.0251
age_group*sample_typ A   2 C   3 0.08058 1.3102 30 0.06 0.9514 Tukey-Kramer 1.0000 0.05 -2.5951 2.7563 -4.2921 4.4532
age_group*sample_typ B   2 C   2 -0.6592 0.3663 30 -1.80 0.0820 Tukey-Kramer 0.6821 0.05 -1.4073 0.08894 -1.8817 0.5634
age_group*sample_typ B   2 A   3 0.4690 1.0939 30 0.43 0.6712 Tukey-Kramer 1.0000 0.05 -1.7651 2.7032 -3.1820 4.1201
age_group*sample_typ B   2 B   3 0.4058 1.0393 30 0.39 0.6989 Tukey-Kramer 1.0000 0.05 -1.7167 2.5284 -3.0628 3.8745
age_group*sample_typ B   2 C   3 -0.2209 1.0597 30 -0.21 0.8363 Tukey-Kramer 1.0000 0.05 -2.3851 1.9432 -3.7576 3.3158
age_group*sample_typ C   2 A   3 1.1282 1.1894 30 0.95 0.3504 Tukey-Kramer 0.9878 0.05 -1.3009 3.5573 -2.8414 5.0978
age_group*sample_typ C   2 B   3 1.0650 1.1393 30 0.93 0.3574 Tukey-Kramer 0.9889 0.05 -1.2618 3.3918 -2.7375 4.8675
age_group*sample_typ C   2 C   3 0.4382 1.1580 30 0.38 0.7078 Tukey-Kramer 1.0000 0.05 -1.9266 2.8031 -3.4265 4.3029
age_group*sample_typ A   3 B   3 -0.06321 0.1937 30 -0.33 0.7464 Tukey-Kramer 1.0000 0.05 -0.4587 0.3323 -0.7096 0.5831
age_group*sample_typ A   3 C   3 -0.6900 0.2564 30 -2.69 0.0115 Tukey-Kramer 0.1936 0.05 -1.2137 -0.1663 -1.5458 0.1658
age_group*sample_typ B   3 C   3 -0.6268 0.1623 30 -3.86 0.0006 Tukey-Kramer 0.0141 0.05 -0.9583 -0.2952 -1.1686 -0.08494
hospbi*age_gr*sample A 3 1 B 3 1 2.1351 0.5352 30 3.99 0.0004 Tukey-Kramer 0.0587 0.05 1.0421 3.2280 -0.03769 4.3078
hospbi*age_gr*sample A 3 1 C 3 1 1.2441 0.7086 30 1.76 0.0893 Tukey-Kramer 0.9849 0.05 -0.2030 2.6913 -1.6327 4.1209
hospbi*age_gr*sample A 3 1 A 3 2 6.5749 2.3688 30 2.78 0.0094 Tukey-Kramer 0.5356 0.05 1.7371 11.4127 -3.0424 16.1923
hospbi*age_gr*sample A 3 1 B 3 2 6.6365 2.0678 30 3.21 0.0032 Tukey-Kramer 0.2828 0.05 2.4135 10.8596 -1.7587 15.0317
hospbi*age_gr*sample A 3 1 C 3 2 6.2310 2.1832 30 2.85 0.0078 Tukey-Kramer 0.4848 0.05 1.7724 10.6896 -2.6325 15.0945
hospbi*age_gr*sample A 3 1 A 3 3 6.8540 1.7568 30 3.90 0.0005 Tukey-Kramer 0.0716 0.05 3.2662 10.4419 -0.2784 13.9865
hospbi*age_gr*sample A 3 1 B 3 3 6.7662 1.6590 30 4.08 0.0003 Tukey-Kramer 0.0479 0.05 3.3780 10.1544 0.03064 13.5018
hospbi*age_gr*sample A 3 1 C 3 3 6.3525 1.6956 30 3.75 0.0008 Tukey-Kramer 0.1003 0.05 2.8896 9.8153 -0.5315 13.2364
hospbi*age_gr*sample A 3 1 A 6 1 3.1963 1.9819 30 1.61 0.1173 Tukey-Kramer 0.9945 0.05 -0.8513 7.2439 -4.8501 11.2428
hospbi*age_gr*sample A 3 1 B 6 1 3.9207 1.8056 30 2.17 0.0379 Tukey-Kramer 0.8867 0.05 0.2332 7.6083 -3.4099 11.2514
hospbi*age_gr*sample A 3 1 C 6 1 2.9047 1.8723 30 1.55 0.1313 Tukey-Kramer 0.9967 0.05 -0.9189 6.7284 -4.6966 10.5060
hospbi*age_gr*sample A 3 1 A 6 2 6.4969 2.3688 30 2.74 0.0102 Tukey-Kramer 0.5572 0.05 1.6591 11.3347 -3.1204 16.1143
hospbi*age_gr*sample A 3 1 B 6 2 7.0150 2.0678 30 3.39 0.0020 Tukey-Kramer 0.2039 0.05 2.7920 11.2381 -1.3802 15.4102
hospbi*age_gr*sample A 3 1 C 6 2 5.8163 2.1832 30 2.66 0.0123 Tukey-Kramer 0.6090 0.05 1.3577 10.2749 -3.0473 14.6798
hospbi*age_gr*sample A 3 1 A 6 3 6.9777 1.7907 30 3.90 0.0005 Tukey-Kramer 0.0723 0.05 3.3207 10.6347 -0.2923 14.2477
hospbi*age_gr*sample A 3 1 B 6 3 6.8360 1.6808 30 4.07 0.0003 Tukey-Kramer 0.0492 0.05 3.4035 10.2686 0.01227 13.6598
hospbi*age_gr*sample A 3 1 C 6 3 6.1631 1.7219 30 3.58 0.0012 Tukey-Kramer 0.1418 0.05 2.6464 9.6797 -0.8278 13.1540
hospbi*age_gr*sample A 3 1 A 9 1 5.3750 1.9819 30 2.71 0.0110 Tukey-Kramer 0.5774 0.05 1.3274 9.4226 -2.6715 13.4214
hospbi*age_gr*sample A 3 1 B 9 1 5.5703 1.8056 30 3.09 0.0043 Tukey-Kramer 0.3468 0.05 1.8828 9.2578 -1.7603 12.9010
hospbi*age_gr*sample A 3 1 C 9 1 4.8638 1.8723 30 2.60 0.0144 Tukey-Kramer 0.6525 0.05 1.0402 8.6875 -2.7375 12.4651
hospbi*age_gr*sample A 3 1 A 9 2 5.3766 2.9964 30 1.79 0.0828 Tukey-Kramer 0.9808 0.05 -0.7428 11.4961 -6.7885 17.5418
hospbi*age_gr*sample A 3 1 B 9 2 5.7015 2.5114 30 2.27 0.0305 Tukey-Kramer 0.8430 0.05 0.5725 10.8305 -4.4947 15.8977
hospbi*age_gr*sample A 3 1 C 9 2 5.3283 2.6996 30 1.97 0.0577 Tukey-Kramer 0.9497 0.05 -0.1850 10.8416 -5.6319 16.2885
hospbi*age_gr*sample A 3 1 A 9 3 6.9285 1.7568 30 3.94 0.0004 Tukey-Kramer 0.0651 0.05 3.3406 10.5163 -0.2040 14.0609
hospbi*age_gr*sample A 3 1 B 9 3 6.9683 1.6590 30 4.20 0.0002 Tukey-Kramer 0.0360 0.05 3.5801 10.3565 0.2327 13.7039
hospbi*age_gr*sample A 3 1 C 9 3 6.1747 1.6956 30 3.64 0.0010 Tukey-Kramer 0.1249 0.05 2.7119 9.6375 -0.7093 13.0586
hospbi*age_gr*sample B 3 1 C 3 1 -0.8909 0.4486 30 -1.99 0.0563 Tukey-Kramer 0.9467 0.05 -1.8072 0.02530 -2.7123 0.9305
hospbi*age_gr*sample B 3 1 A 3 2 4.4398 2.1728 30 2.04 0.0499 Tukey-Kramer 0.9312 0.05 0.002415 8.8773 -4.3816 13.2613
hospbi*age_gr*sample B 3 1 B 3 2 4.5015 1.8400 30 2.45 0.0205 Tukey-Kramer 0.7474 0.05 0.7437 8.2592 -2.9687 11.9716
hospbi*age_gr*sample B 3 1 C 3 2 4.0959 1.9687 30 2.08 0.0461 Tukey-Kramer 0.9197 0.05 0.07528 8.1166 -3.8969 12.0888
hospbi*age_gr*sample B 3 1 A 3 3 4.7190 1.4819 30 3.18 0.0034 Tukey-Kramer 0.2950 0.05 1.6926 7.7453 -1.2973 10.7352
hospbi*age_gr*sample B 3 1 B 3 3 4.6311 1.3646 30 3.39 0.0020 Tukey-Kramer 0.2033 0.05 1.8443 7.4179 -0.9089 10.1712
hospbi*age_gr*sample B 3 1 C 3 3 4.2174 1.4088 30 2.99 0.0055 Tukey-Kramer 0.3988 0.05 1.3403 7.0945 -1.5021 9.9369
hospbi*age_gr*sample B 3 1 A 6 1 1.0613 1.7429 30 0.61 0.5472 Tukey-Kramer 1.0000 0.05 -2.4982 4.6207 -6.0147 8.1372
hospbi*age_gr*sample B 3 1 B 6 1 1.7857 1.5394 30 1.16 0.2552 Tukey-Kramer 1.0000 0.05 -1.3583 4.9296 -4.4643 8.0357
hospbi*age_gr*sample B 3 1 C 6 1 0.7697 1.6171 30 0.48 0.6376 Tukey-Kramer 1.0000 0.05 -2.5329 4.0722 -5.7957 7.3350
hospbi*age_gr*sample B 3 1 A 6 2 4.3619 2.1728 30 2.01 0.0538 Tukey-Kramer 0.9412 0.05 -0.07558 8.7993 -4.4596 13.1833
hospbi*age_gr*sample B 3 1 B 6 2 4.8799 1.8400 30 2.65 0.0127 Tukey-Kramer 0.6169 0.05 1.1222 8.6377 -2.5902 12.3501
hospbi*age_gr*sample B 3 1 C 6 2 3.6812 1.9687 30 1.87 0.0713 Tukey-Kramer 0.9703 0.05 -0.3394 7.7019 -4.3117 11.6741
hospbi*age_gr*sample B 3 1 A 6 3 4.8426 1.5219 30 3.18 0.0034 Tukey-Kramer 0.2962 0.05 1.7345 7.9507 -1.3362 11.0214
hospbi*age_gr*sample B 3 1 B 6 3 4.7010 1.3909 30 3.38 0.0020 Tukey-Kramer 0.2087 0.05 1.8604 7.5415 -0.9460 10.3479
hospbi*age_gr*sample B 3 1 C 6 3 4.0280 1.4404 30 2.80 0.0089 Tukey-Kramer 0.5219 0.05 1.0864 6.9696 -1.8198 9.8758
hospbi*age_gr*sample B 3 1 A 9 1 3.2399 1.7429 30 1.86 0.0729 Tukey-Kramer 0.9720 0.05 -0.3195 6.7993 -3.8361 10.3159
hospbi*age_gr*sample B 3 1 B 9 1 3.4352 1.5394 30 2.23 0.0333 Tukey-Kramer 0.8611 0.05 0.2913 6.5792 -2.8148 9.6852
hospbi*age_gr*sample B 3 1 C 9 1 2.7288 1.6171 30 1.69 0.1019 Tukey-Kramer 0.9904 0.05 -0.5738 6.0313 -3.8366 9.2941
hospbi*age_gr*sample B 3 1 A 9 2 3.2416 2.8439 30 1.14 0.2634 Tukey-Kramer 1.0000 0.05 -2.5665 9.0496 -8.3046 14.7877
hospbi*age_gr*sample B 3 1 B 9 2 3.5664 2.3274 30 1.53 0.1359 Tukey-Kramer 0.9972 0.05 -1.1867 8.3196 -5.8827 13.0155
hospbi*age_gr*sample B 3 1 C 9 2 3.1932 2.5293 30 1.26 0.2165 Tukey-Kramer 0.9998 0.05 -1.9723 8.3588 -7.0757 13.4621
hospbi*age_gr*sample B 3 1 A 9 3 4.7934 1.4819 30 3.23 0.0030 Tukey-Kramer 0.2708 0.05 1.7670 7.8197 -1.2229 10.8096
hospbi*age_gr*sample B 3 1 B 9 3 4.8333 1.3646 30 3.54 0.0013 Tukey-Kramer 0.1528 0.05 2.0465 7.6200 -0.7068 10.3733
hospbi*age_gr*sample B 3 1 C 9 3 4.0396 1.4088 30 2.87 0.0075 Tukey-Kramer 0.4762 0.05 1.1625 6.9167 -1.6799 9.7591
hospbi*age_gr*sample C 3 1 A 3 2 5.3308 2.2468 30 2.37 0.0243 Tukey-Kramer 0.7899 0.05 0.7423 9.9193 -3.7910 14.4525
hospbi*age_gr*sample C 3 1 B 3 2 5.3924 1.9268 30 2.80 0.0089 Tukey-Kramer 0.5205 0.05 1.4574 9.3273 -2.4301 13.2149
hospbi*age_gr*sample C 3 1 C 3 2 4.9869 2.0501 30 2.43 0.0212 Tukey-Kramer 0.7556 0.05 0.8001 9.1736 -3.3363 13.3100
hospbi*age_gr*sample C 3 1 A 3 3 5.6099 1.5883 30 3.53 0.0014 Tukey-Kramer 0.1559 0.05 2.3661 8.8537 -0.8387 12.0584
hospbi*age_gr*sample C 3 1 B 3 3 5.5221 1.4795 30 3.73 0.0008 Tukey-Kramer 0.1033 0.05 2.5005 8.5436 -0.4846 11.5288
hospbi*age_gr*sample C 3 1 C 3 3 5.1083 1.5204 30 3.36 0.0021 Tukey-Kramer 0.2166 0.05 2.0033 8.2133 -1.0643 11.2809
hospbi*age_gr*sample C 3 1 A 6 1 1.9522 1.8343 30 1.06 0.2957 Tukey-Kramer 1.0000 0.05 -1.7939 5.6983 -5.4948 9.3992
hospbi*age_gr*sample C 3 1 B 6 1 2.6766 1.6422 30 1.63 0.1136 Tukey-Kramer 0.9937 0.05 -0.6772 6.0304 -3.9905 9.3437
hospbi*age_gr*sample C 3 1 C 6 1 1.6606 1.7152 30 0.97 0.3407 Tukey-Kramer 1.0000 0.05 -1.8423 5.1635 -5.3030 8.6242
hospbi*age_gr*sample C 3 1 A 6 2 5.2528 2.2468 30 2.34 0.0263 Tukey-Kramer 0.8087 0.05 0.6643 9.8413 -3.8689 14.3745
hospbi*age_gr*sample C 3 1 B 6 2 5.7709 1.9268 30 3.00 0.0055 Tukey-Kramer 0.3979 0.05 1.8359 9.7058 -2.0516 13.5934
hospbi*age_gr*sample C 3 1 C 6 2 4.5721 2.0501 30 2.23 0.0334 Tukey-Kramer 0.8617 0.05 0.3854 8.7589 -3.7510 12.8953
hospbi*age_gr*sample C 3 1 A 6 3 5.7336 1.6257 30 3.53 0.0014 Tukey-Kramer 0.1575 0.05 2.4133 9.0538 -0.8669 12.3340
hospbi*age_gr*sample C 3 1 B 6 3 5.5919 1.5038 30 3.72 0.0008 Tukey-Kramer 0.1064 0.05 2.5207 8.6631 -0.5135 11.6973
hospbi*age_gr*sample C 3 1 C 6 3 4.9189 1.5497 30 3.17 0.0035 Tukey-Kramer 0.3001 0.05 1.7540 8.0838 -1.3727 11.2106
hospbi*age_gr*sample C 3 1 A 9 1 4.1308 1.8343 30 2.25 0.0318 Tukey-Kramer 0.8517 0.05 0.3848 7.8769 -3.3162 11.5778
hospbi*age_gr*sample C 3 1 B 9 1 4.3262 1.6422 30 2.63 0.0132 Tukey-Kramer 0.6286 0.05 0.9724 7.6799 -2.3410 10.9933
hospbi*age_gr*sample C 3 1 C 9 1 3.6197 1.7152 30 2.11 0.0433 Tukey-Kramer 0.9097 0.05 0.1168 7.1226 -3.3439 10.5833
hospbi*age_gr*sample C 3 1 A 9 2 4.1325 2.9008 30 1.42 0.1646 Tukey-Kramer 0.9990 0.05 -1.7918 10.0568 -7.6447 15.9097
hospbi*age_gr*sample C 3 1 B 9 2 4.4574 2.3966 30 1.86 0.0727 Tukey-Kramer 0.9719 0.05 -0.4371 9.3519 -5.2727 14.1874
hospbi*age_gr*sample C 3 1 C 9 2 4.0842 2.5931 30 1.57 0.1257 Tukey-Kramer 0.9960 0.05 -1.2117 9.3800 -6.4439 14.6122
hospbi*age_gr*sample C 3 1 A 9 3 5.6843 1.5883 30 3.58 0.0012 Tukey-Kramer 0.1420 0.05 2.4405 8.9281 -0.7642 12.1329
hospbi*age_gr*sample C 3 1 B 9 3 5.7242 1.4795 30 3.87 0.0005 Tukey-Kramer 0.0769 0.05 2.7026 8.7457 -0.2825 11.7309
hospbi*age_gr*sample C 3 1 C 9 3 4.9305 1.5204 30 3.24 0.0029 Tukey-Kramer 0.2669 0.05 1.8255 8.0355 -1.2421 11.1031
hospbi*age_gr*sample A 3 2 B 3 2 0.06161 0.6554 30 0.09 0.9257 Tukey-Kramer 1.0000 0.05 -1.2770 1.4002 -2.5995 2.7227
hospbi*age_gr*sample A 3 2 C 3 2 -0.3439 0.8678 30 -0.40 0.6947 Tukey-Kramer 1.0000 0.05 -2.1163 1.4284 -3.8673 3.1794
hospbi*age_gr*sample A 3 2 A 3 3 0.2791 2.0515 30 0.14 0.8927 Tukey-Kramer 1.0000 0.05 -3.9105 4.4688 -8.0498 8.6080
hospbi*age_gr*sample A 3 2 B 3 3 0.1913 1.9684 30 0.10 0.9232 Tukey-Kramer 1.0000 0.05 -3.8287 4.2113 -7.8004 8.1830
hospbi*age_gr*sample A 3 2 C 3 3 -0.2225 1.9993 30 -0.11 0.9121 Tukey-Kramer 1.0000 0.05 -4.3056 3.8607 -8.3396 7.8946
hospbi*age_gr*sample A 3 2 A 6 1 -3.3786 2.2473 30 -1.50 0.1432 Tukey-Kramer 0.9978 0.05 -7.9681 1.2110 -12.5024 5.7452
hospbi*age_gr*sample A 3 2 B 6 1 -2.6542 2.0934 30 -1.27 0.2146 Tukey-Kramer 0.9998 0.05 -6.9295 1.6212 -11.1534 5.8451
hospbi*age_gr*sample A 3 2 C 6 1 -3.6702 2.1512 30 -1.71 0.0983 Tukey-Kramer 0.9891 0.05 -8.0635 0.7232 -12.4039 5.0636
hospbi*age_gr*sample A 3 2 A 6 2 -0.07799 2.5949 30 -0.03 0.9762 Tukey-Kramer 1.0000 0.05 -5.3776 5.2216 -10.6133 10.4573
hospbi*age_gr*sample A 3 2 B 6 2 0.4401 2.3234 30 0.19 0.8510 Tukey-Kramer 1.0000 0.05 -4.3049 5.1851 -8.9927 9.8729
hospbi*age_gr*sample A 3 2 C 6 2 -0.7586 2.4266 30 -0.31 0.7567 Tukey-Kramer 1.0000 0.05 -5.7145 4.1972 -10.6106 9.0933
hospbi*age_gr*sample A 3 2 A 6 3 0.4028 2.0806 30 0.19 0.8478 Tukey-Kramer 1.0000 0.05 -3.8463 4.6519 -8.0442 8.8498
hospbi*age_gr*sample A 3 2 B 6 3 0.2611 1.9868 30 0.13 0.8963 Tukey-Kramer 1.0000 0.05 -3.7964 4.3186 -7.8050 8.3272
hospbi*age_gr*sample A 3 2 C 6 3 -0.4118 2.0217 30 -0.20 0.8400 Tukey-Kramer 1.0000 0.05 -4.5407 3.7170 -8.6199 7.7962
hospbi*age_gr*sample A 3 2 A 9 1 -1.1999 2.2473 30 -0.53 0.5973 Tukey-Kramer 1.0000 0.05 -5.7895 3.3896 -10.3238 7.9239
hospbi*age_gr*sample A 3 2 B 9 1 -1.0046 2.0934 30 -0.48 0.6348 Tukey-Kramer 1.0000 0.05 -5.2800 3.2708 -9.5039 7.4946
hospbi*age_gr*sample A 3 2 C 9 1 -1.7111 2.1512 30 -0.80 0.4326 Tukey-Kramer 1.0000 0.05 -6.1044 2.6823 -10.4448 7.0227
hospbi*age_gr*sample A 3 2 A 9 2 -1.1983 3.1781 30 -0.38 0.7088 Tukey-Kramer 1.0000 0.05 -7.6889 5.2923 -14.1013 11.7048
hospbi*age_gr*sample A 3 2 B 9 2 -0.8734 2.7257 30 -0.32 0.7509 Tukey-Kramer 1.0000 0.05 -6.4400 4.6932 -11.9396 10.1928
hospbi*age_gr*sample A 3 2 C 9 2 -1.2466 2.9000 30 -0.43 0.6704 Tukey-Kramer 1.0000 0.05 -7.1693 4.6760 -13.0206 10.5273
hospbi*age_gr*sample A 3 2 A 9 3 0.3535 2.0515 30 0.17 0.8643 Tukey-Kramer 1.0000 0.05 -3.8361 4.5432 -7.9753 8.6824
hospbi*age_gr*sample A 3 2 B 9 3 0.3934 1.9684 30 0.20 0.8429 Tukey-Kramer 1.0000 0.05 -3.6266 4.4134 -7.5983 8.3851
hospbi*age_gr*sample A 3 2 C 9 3 -0.4002 1.9993 30 -0.20 0.8427 Tukey-Kramer 1.0000 0.05 -4.4834 3.6829 -8.5173 7.7169
hospbi*age_gr*sample B 3 2 C 3 2 -0.4055 0.5495 30 -0.74 0.4662 Tukey-Kramer 1.0000 0.05 -1.5277 0.7166 -2.6363 1.8252
hospbi*age_gr*sample B 3 2 A 3 3 0.2175 1.6950 30 0.13 0.8987 Tukey-Kramer 1.0000 0.05 -3.2441 3.6791 -6.6641 7.0991
hospbi*age_gr*sample B 3 2 B 3 3 0.1297 1.5935 30 0.08 0.9357 Tukey-Kramer 1.0000 0.05 -3.1246 3.3840 -6.3397 6.5990
hospbi*age_gr*sample B 3 2 C 3 3 -0.2841 1.6315 30 -0.17 0.8629 Tukey-Kramer 1.0000 0.05 -3.6160 3.0478 -6.9077 6.3396
hospbi*age_gr*sample B 3 2 A 6 1 -3.4402 1.9274 30 -1.78 0.0844 Tukey-Kramer 0.9818 0.05 -7.3764 0.4960 -11.2652 4.3848
hospbi*age_gr*sample B 3 2 B 6 1 -2.7158 1.7455 30 -1.56 0.1302 Tukey-Kramer 0.9966 0.05 -6.2807 0.8491 -9.8026 4.3710
hospbi*age_gr*sample B 3 2 C 6 1 -3.7318 1.8144 30 -2.06 0.0485 Tukey-Kramer 0.9272 0.05 -7.4373 -0.02625 -11.0982 3.6346
hospbi*age_gr*sample B 3 2 A 6 2 -0.1396 2.3234 30 -0.06 0.9525 Tukey-Kramer 1.0000 0.05 -4.8846 4.6054 -9.5724 9.2932
hospbi*age_gr*sample B 3 2 B 6 2 0.3785 2.0156 30 0.19 0.8523 Tukey-Kramer 1.0000 0.05 -3.7379 4.4949 -7.8047 8.5617
hospbi*age_gr*sample B 3 2 C 6 2 -0.8203 2.1338 30 -0.38 0.7034 Tukey-Kramer 1.0000 0.05 -5.1780 3.5375 -9.4832 7.8427
hospbi*age_gr*sample B 3 2 A 6 3 0.3412 1.7301 30 0.20 0.8450 Tukey-Kramer 1.0000 0.05 -3.1922 3.8745 -6.6829 7.3653
hospbi*age_gr*sample B 3 2 B 6 3 0.1995 1.6161 30 0.12 0.9026 Tukey-Kramer 1.0000 0.05 -3.1009 3.4999 -6.3616 6.7606
hospbi*age_gr*sample B 3 2 C 6 3 -0.4734 1.6588 30 -0.29 0.7773 Tukey-Kramer 1.0000 0.05 -3.8613 2.9144 -7.2083 6.2614
hospbi*age_gr*sample B 3 2 A 9 1 -1.2615 1.9274 30 -0.65 0.5177 Tukey-Kramer 1.0000 0.05 -5.1977 2.6746 -9.0865 6.5634
hospbi*age_gr*sample B 3 2 B 9 1 -1.0662 1.7455 30 -0.61 0.5459 Tukey-Kramer 1.0000 0.05 -4.6311 2.4987 -8.1530 6.0206
hospbi*age_gr*sample B 3 2 C 9 1 -1.7727 1.8144 30 -0.98 0.3364 Tukey-Kramer 1.0000 0.05 -5.4782 1.9328 -9.1391 5.5938
hospbi*age_gr*sample B 3 2 A 9 2 -1.2599 2.9606 30 -0.43 0.6735 Tukey-Kramer 1.0000 0.05 -7.3062 4.7864 -13.2796 10.7599
hospbi*age_gr*sample B 3 2 B 9 2 -0.9350 2.4686 30 -0.38 0.7075 Tukey-Kramer 1.0000 0.05 -5.9765 4.1065 -10.9573 9.0873
hospbi*age_gr*sample B 3 2 C 9 2 -1.3082 2.6598 30 -0.49 0.6264 Tukey-Kramer 1.0000 0.05 -6.7403 4.1238 -12.1069 9.4904
hospbi*age_gr*sample B 3 2 A 9 3 0.2919 1.6950 30 0.17 0.8644 Tukey-Kramer 1.0000 0.05 -3.1697 3.7536 -6.5896 7.1735
hospbi*age_gr*sample B 3 2 B 9 3 0.3318 1.5935 30 0.21 0.8365 Tukey-Kramer 1.0000 0.05 -2.9225 3.5861 -6.1376 6.8012
hospbi*age_gr*sample B 3 2 C 9 3 -0.4618 1.6315 30 -0.28 0.7791 Tukey-Kramer 1.0000 0.05 -3.7938 2.8701 -7.0855 6.1618
hospbi*age_gr*sample C 3 2 A 3 3 0.6230 1.8339 30 0.34 0.7364 Tukey-Kramer 1.0000 0.05 -3.1224 4.3685 -6.8227 8.0688
hospbi*age_gr*sample C 3 2 B 3 3 0.5352 1.7405 30 0.31 0.7606 Tukey-Kramer 1.0000 0.05 -3.0194 4.0899 -6.5313 7.6017
hospbi*age_gr*sample C 3 2 C 3 3 0.1215 1.7754 30 0.07 0.9459 Tukey-Kramer 1.0000 0.05 -3.5044 3.7473 -7.0866 7.3295
hospbi*age_gr*sample C 3 2 A 6 1 -3.0347 2.0506 30 -1.48 0.1493 Tukey-Kramer 0.9983 0.05 -7.2226 1.1533 -11.3601 5.2908
hospbi*age_gr*sample C 3 2 B 6 1 -2.3103 1.8808 30 -1.23 0.2289 Tukey-Kramer 0.9999 0.05 -6.1513 1.5308 -9.9461 5.3256
hospbi*age_gr*sample C 3 2 C 6 1 -3.3263 1.9449 30 -1.71 0.0975 Tukey-Kramer 0.9888 0.05 -7.2982 0.6457 -11.2223 4.5698
hospbi*age_gr*sample C 3 2 A 6 2 0.2659 2.4266 30 0.11 0.9135 Tukey-Kramer 1.0000 0.05 -4.6899 5.2217 -9.5860 10.1179
hospbi*age_gr*sample C 3 2 B 6 2 0.7840 2.1338 30 0.37 0.7159 Tukey-Kramer 1.0000 0.05 -3.5737 5.1417 -7.8789 9.4470
hospbi*age_gr*sample C 3 2 C 6 2 -0.4147 2.2457 30 -0.18 0.8547 Tukey-Kramer 1.0000 0.05 -5.0011 4.1717 -9.5322 8.7028
hospbi*age_gr*sample C 3 2 A 6 3 0.7467 1.8664 30 0.40 0.6919 Tukey-Kramer 1.0000 0.05 -3.0651 4.5585 -6.8309 8.3244
hospbi*age_gr*sample C 3 2 B 6 3 0.6050 1.7613 30 0.34 0.7336 Tukey-Kramer 1.0000 0.05 -2.9919 4.2020 -6.5455 7.7556
hospbi*age_gr*sample C 3 2 C 6 3 -0.06791 1.8006 30 -0.04 0.9702 Tukey-Kramer 1.0000 0.05 -3.7452 3.6094 -7.3782 7.2424
hospbi*age_gr*sample C 3 2 A 9 1 -0.8560 2.0506 30 -0.42 0.6793 Tukey-Kramer 1.0000 0.05 -5.0439 3.3319 -9.1814 7.4694
hospbi*age_gr*sample C 3 2 B 9 1 -0.6607 1.8808 30 -0.35 0.7278 Tukey-Kramer 1.0000 0.05 -4.5017 3.1804 -8.2965 6.9751
hospbi*age_gr*sample C 3 2 C 9 1 -1.3671 1.9449 30 -0.70 0.4875 Tukey-Kramer 1.0000 0.05 -5.3391 2.6048 -9.2632 6.5289
hospbi*age_gr*sample C 3 2 A 9 2 -0.8543 3.0423 30 -0.28 0.7808 Tukey-Kramer 1.0000 0.05 -7.0675 5.3588 -13.2057 11.4971
hospbi*age_gr*sample C 3 2 B 9 2 -0.5295 2.5660 30 -0.21 0.8379 Tukey-Kramer 1.0000 0.05 -5.7699 4.7109 -10.9472 9.8882
hospbi*age_gr*sample C 3 2 C 9 2 -0.9027 2.7504 30 -0.33 0.7450 Tukey-Kramer 1.0000 0.05 -6.5198 4.7144 -12.0693 10.2639
hospbi*age_gr*sample C 3 2 A 9 3 0.6975 1.8339 30 0.38 0.7064 Tukey-Kramer 1.0000 0.05 -3.0479 4.4429 -6.7482 8.1432
hospbi*age_gr*sample C 3 2 B 9 3 0.7373 1.7405 30 0.42 0.6749 Tukey-Kramer 1.0000 0.05 -2.8173 4.2920 -6.3291 7.8038
hospbi*age_gr*sample C 3 2 C 9 3 -0.05631 1.7754 30 -0.03 0.9749 Tukey-Kramer 1.0000 0.05 -3.6822 3.5695 -7.2643 7.1517
hospbi*age_gr*sample A 3 3 B 3 3 -0.08783 0.3277 30 -0.27 0.7905 Tukey-Kramer 1.0000 0.05 -0.7571 0.5815 -1.4184 1.2427
hospbi*age_gr*sample A 3 3 C 3 3 -0.5016 0.4339 30 -1.16 0.2568 Tukey-Kramer 1.0000 0.05 -1.3877 0.3846 -2.2632 1.2601
hospbi*age_gr*sample A 3 3 A 6 1 -3.6577 1.5891 30 -2.30 0.0285 Tukey-Kramer 0.8275 0.05 -6.9030 -0.4124 -10.1092 2.7938
hospbi*age_gr*sample A 3 3 B 6 1 -2.9333 1.3628 30 -2.15 0.0395 Tukey-Kramer 0.8943 0.05 -5.7166 -0.1500 -8.4664 2.5998
hospbi*age_gr*sample A 3 3 C 6 1 -3.9493 1.4500 30 -2.72 0.0107 Tukey-Kramer 0.5698 0.05 -6.9106 -0.9880 -9.8363 1.9377
hospbi*age_gr*sample A 3 3 A 6 2 -0.3571 2.0515 30 -0.17 0.8630 Tukey-Kramer 1.0000 0.05 -4.5468 3.8326 -8.6860 7.9718
hospbi*age_gr*sample A 3 3 B 6 2 0.1610 1.6950 30 0.09 0.9250 Tukey-Kramer 1.0000 0.05 -3.3007 3.6226 -6.7206 7.0426
hospbi*age_gr*sample A 3 3 C 6 2 -1.0378 1.8339 30 -0.57 0.5757 Tukey-Kramer 1.0000 0.05 -4.7832 2.7076 -8.4835 6.4079
hospbi*age_gr*sample A 3 3 A 6 3 0.1237 1.3430 30 0.09 0.9272 Tukey-Kramer 1.0000 0.05 -2.6191 2.8664 -5.3289 5.5762
hospbi*age_gr*sample A 3 3 B 6 3 -0.01801 1.1925 30 -0.02 0.9881 Tukey-Kramer 1.0000 0.05 -2.4534 2.4174 -4.8595 4.8235
hospbi*age_gr*sample A 3 3 C 6 3 -0.6910 1.2499 30 -0.55 0.5845 Tukey-Kramer 1.0000 0.05 -3.2435 1.8616 -5.7654 4.3835
hospbi*age_gr*sample A 3 3 A 9 1 -1.4791 1.5891 30 -0.93 0.3594 Tukey-Kramer 1.0000 0.05 -4.7244 1.7662 -7.9306 4.9725
hospbi*age_gr*sample A 3 3 B 9 1 -1.2837 1.3628 30 -0.94 0.3537 Tukey-Kramer 1.0000 0.05 -4.0670 1.4996 -6.8168 4.2494
hospbi*age_gr*sample A 3 3 C 9 1 -1.9902 1.4500 30 -1.37 0.1801 Tukey-Kramer 0.9994 0.05 -4.9515 0.9711 -7.8772 3.8968
hospbi*age_gr*sample A 3 3 A 9 2 -1.4774 2.7523 30 -0.54 0.5954 Tukey-Kramer 1.0000 0.05 -7.0984 4.1436 -12.6518 9.6970
hospbi*age_gr*sample A 3 3 B 9 2 -1.1525 2.2146 30 -0.52 0.6066 Tukey-Kramer 1.0000 0.05 -5.6753 3.3702 -10.1435 7.8385
hospbi*age_gr*sample A 3 3 C 9 2 -1.5257 2.4259 30 -0.63 0.5341 Tukey-Kramer 1.0000 0.05 -6.4801 3.4286 -11.3748 8.3233
hospbi*age_gr*sample A 3 3 A 9 3 0.07442 1.2975 30 0.06 0.9546 Tukey-Kramer 1.0000 0.05 -2.5754 2.7242 -5.1932 5.3421
hospbi*age_gr*sample A 3 3 B 9 3 0.1143 1.1617 30 0.10 0.9223 Tukey-Kramer 1.0000 0.05 -2.2582 2.4868 -4.6021 4.8307
hospbi*age_gr*sample A 3 3 C 9 3 -0.6794 1.2133 30 -0.56 0.5797 Tukey-Kramer 1.0000 0.05 -3.1573 1.7986 -5.6053 4.2466
hospbi*age_gr*sample B 3 3 C 3 3 -0.4137 0.2747 30 -1.51 0.1425 Tukey-Kramer 0.9978 0.05 -0.9748 0.1473 -1.5291 0.7016
hospbi*age_gr*sample B 3 3 A 6 1 -3.5699 1.4803 30 -2.41 0.0222 Tukey-Kramer 0.7678 0.05 -6.5930 -0.5467 -9.5798 2.4400
hospbi*age_gr*sample B 3 3 B 6 1 -2.8455 1.2343 30 -2.31 0.0282 Tukey-Kramer 0.8257 0.05 -5.3662 -0.3247 -7.8566 2.1657
hospbi*age_gr*sample B 3 3 C 6 1 -3.8615 1.3299 30 -2.90 0.0069 Tukey-Kramer 0.4535 0.05 -6.5775 -1.1454 -9.2608 1.5379
hospbi*age_gr*sample B 3 3 A 6 2 -0.2693 1.9684 30 -0.14 0.8921 Tukey-Kramer 1.0000 0.05 -4.2893 3.7508 -8.2609 7.7224
hospbi*age_gr*sample B 3 3 B 6 2 0.2488 1.5935 30 0.16 0.8770 Tukey-Kramer 1.0000 0.05 -3.0055 3.5031 -6.2205 6.7182
hospbi*age_gr*sample B 3 3 C 6 2 -0.9499 1.7405 30 -0.55 0.5893 Tukey-Kramer 1.0000 0.05 -4.5046 2.6047 -8.0164 6.1165
hospbi*age_gr*sample B 3 3 A 6 3 0.2115 1.2123 30 0.17 0.8627 Tukey-Kramer 1.0000 0.05 -2.2644 2.6874 -4.7106 5.1335
hospbi*age_gr*sample B 3 3 B 6 3 0.06982 1.0432 30 0.07 0.9471 Tukey-Kramer 1.0000 0.05 -2.0606 2.2002 -4.1654 4.3050
hospbi*age_gr*sample B 3 3 C 6 3 -0.6031 1.1083 30 -0.54 0.5903 Tukey-Kramer 1.0000 0.05 -2.8665 1.6603 -5.1027 3.8964
hospbi*age_gr*sample B 3 3 A 9 1 -1.3912 1.4803 30 -0.94 0.3548 Tukey-Kramer 1.0000 0.05 -4.4144 1.6319 -7.4011 4.6186
hospbi*age_gr*sample B 3 3 B 9 1 -1.1959 1.2343 30 -0.97 0.3403 Tukey-Kramer 1.0000 0.05 -3.7167 1.3248 -6.2070 3.8152
hospbi*age_gr*sample B 3 3 C 9 1 -1.9024 1.3299 30 -1.43 0.1629 Tukey-Kramer 0.9989 0.05 -4.6184 0.8137 -7.3017 3.4970
hospbi*age_gr*sample B 3 3 A 9 2 -1.3896 2.6910 30 -0.52 0.6094 Tukey-Kramer 1.0000 0.05 -6.8853 4.1062 -12.3149 9.5358
hospbi*age_gr*sample B 3 3 B 9 2 -1.0647 2.1378 30 -0.50 0.6221 Tukey-Kramer 1.0000 0.05 -5.4308 3.3014 -9.7443 7.6148
hospbi*age_gr*sample B 3 3 C 9 2 -1.4379 2.3561 30 -0.61 0.5463 Tukey-Kramer 1.0000 0.05 -6.2497 3.3738 -11.0035 8.1276
hospbi*age_gr*sample B 3 3 A 9 3 0.1622 1.1617 30 0.14 0.8899 Tukey-Kramer 1.0000 0.05 -2.2102 2.5347 -4.5542 4.8787
hospbi*age_gr*sample B 3 3 B 9 3 0.2021 1.0078 30 0.20 0.8424 Tukey-Kramer 1.0000 0.05 -1.8561 2.2603 -3.8895 4.2937
hospbi*age_gr*sample B 3 3 C 9 3 -0.5915 1.0669 30 -0.55 0.5834 Tukey-Kramer 1.0000 0.05 -2.7704 1.5873 -4.9230 3.7399
hospbi*age_gr*sample C 3 3 A 6 1 -3.1561 1.5211 30 -2.07 0.0467 Tukey-Kramer 0.9216 0.05 -6.2627 -0.04957 -9.3318 3.0196
hospbi*age_gr*sample C 3 3 B 6 1 -2.4317 1.2830 30 -1.90 0.0677 Tukey-Kramer 0.9659 0.05 -5.0519 0.1885 -7.6406 2.7771
hospbi*age_gr*sample C 3 3 C 6 1 -3.4477 1.3752 30 -2.51 0.0178 Tukey-Kramer 0.7104 0.05 -6.2563 -0.6392 -9.0310 2.1356
hospbi*age_gr*sample C 3 3 A 6 2 0.1445 1.9993 30 0.07 0.9429 Tukey-Kramer 1.0000 0.05 -3.9387 4.2276 -7.9726 8.2616
hospbi*age_gr*sample C 3 3 B 6 2 0.6626 1.6315 30 0.41 0.6875 Tukey-Kramer 1.0000 0.05 -2.6694 3.9945 -5.9611 7.2862
hospbi*age_gr*sample C 3 3 C 6 2 -0.5362 1.7754 30 -0.30 0.7647 Tukey-Kramer 1.0000 0.05 -4.1620 3.0897 -7.7442 6.6718
hospbi*age_gr*sample C 3 3 A 6 3 0.6252 1.2619 30 0.50 0.6239 Tukey-Kramer 1.0000 0.05 -1.9519 3.2024 -4.4980 5.7484
hospbi*age_gr*sample C 3 3 B 6 3 0.4836 1.1004 30 0.44 0.6635 Tukey-Kramer 1.0000 0.05 -1.7637 2.7308 -3.9838 4.9509
hospbi*age_gr*sample C 3 3 C 6 3 -0.1894 1.1623 30 -0.16 0.8717 Tukey-Kramer 1.0000 0.05 -2.5631 2.1843 -4.9081 4.5294
hospbi*age_gr*sample C 3 3 A 9 1 -0.9775 1.5211 30 -0.64 0.5254 Tukey-Kramer 1.0000 0.05 -4.0840 2.1291 -7.1532 5.1982
hospbi*age_gr*sample C 3 3 B 9 1 -0.7822 1.2830 30 -0.61 0.5467 Tukey-Kramer 1.0000 0.05 -3.4024 1.8381 -5.9910 4.4267
hospbi*age_gr*sample C 3 3 C 9 1 -1.4886 1.3752 30 -1.08 0.2877 Tukey-Kramer 1.0000 0.05 -4.2972 1.3200 -7.0719 4.0947
hospbi*age_gr*sample C 3 3 A 9 2 -0.9758 2.7137 30 -0.36 0.7217 Tukey-Kramer 1.0000 0.05 -6.5179 4.5663 -11.9932 10.0416
hospbi*age_gr*sample C 3 3 B 9 2 -0.6510 2.1663 30 -0.30 0.7659 Tukey-Kramer 1.0000 0.05 -5.0752 3.7733 -9.4461 8.1442
hospbi*age_gr*sample C 3 3 C 9 2 -1.0242 2.3819 30 -0.43 0.6703 Tukey-Kramer 1.0000 0.05 -5.8888 3.8404 -10.6948 8.6464
hospbi*age_gr*sample C 3 3 A 9 3 0.5760 1.2133 30 0.47 0.6384 Tukey-Kramer 1.0000 0.05 -1.9019 3.0539 -4.3500 5.5020
hospbi*age_gr*sample C 3 3 B 9 3 0.6159 1.0669 30 0.58 0.5681 Tukey-Kramer 1.0000 0.05 -1.5630 2.7947 -3.7156 4.9473
hospbi*age_gr*sample C 3 3 C 9 3 -0.1778 1.1229 30 -0.16 0.8753 Tukey-Kramer 1.0000 0.05 -2.4710 2.1154 -4.7365 4.3810
hospbi*age_gr*sample A 6 1 B 6 1 0.7244 0.4635 30 1.56 0.1285 Tukey-Kramer 0.9963 0.05 -0.2221 1.6709 -1.1573 2.6061
hospbi*age_gr*sample A 6 1 C 6 1 -0.2916 0.6136 30 -0.48 0.6381 Tukey-Kramer 1.0000 0.05 -1.5448 0.9616 -2.7830 2.1998
hospbi*age_gr*sample A 6 1 A 6 2 3.3006 2.2473 30 1.47 0.1523 Tukey-Kramer 0.9984 0.05 -1.2890 7.8901 -5.8232 12.4244
hospbi*age_gr*sample A 6 1 B 6 2 3.8187 1.9274 30 1.98 0.0568 Tukey-Kramer 0.9478 0.05 -0.1175 7.7549 -4.0063 11.6437
hospbi*age_gr*sample A 6 1 C 6 2 2.6199 2.0506 30 1.28 0.2112 Tukey-Kramer 0.9998 0.05 -1.5680 6.8079 -5.7055 10.9454
hospbi*age_gr*sample A 6 1 A 6 3 3.7814 1.6265 30 2.32 0.0270 Tukey-Kramer 0.8156 0.05 0.4597 7.1030 -2.8220 10.3847
hospbi*age_gr*sample A 6 1 B 6 3 3.6397 1.5046 30 2.42 0.0218 Tukey-Kramer 0.7635 0.05 0.5669 6.7125 -2.4689 9.7482
hospbi*age_gr*sample A 6 1 C 6 3 2.9667 1.5504 30 1.91 0.0653 Tukey-Kramer 0.9626 0.05 -0.1997 6.1332 -3.3280 9.2615
hospbi*age_gr*sample A 6 1 A 9 1 2.1786 1.8349 30 1.19 0.2444 Tukey-Kramer 0.9999 0.05 -1.5687 5.9260 -5.2709 9.6282
hospbi*age_gr*sample A 6 1 B 9 1 2.3740 1.6429 30 1.45 0.1588 Tukey-Kramer 0.9988 0.05 -0.9812 5.7292 -4.2960 9.0440
hospbi*age_gr*sample A 6 1 C 9 1 1.6675 1.7159 30 0.97 0.3389 Tukey-Kramer 1.0000 0.05 -1.8368 5.1718 -5.2989 8.6339
hospbi*age_gr*sample A 6 1 A 9 2 2.1803 2.9012 30 0.75 0.4582 Tukey-Kramer 1.0000 0.05 -3.7448 8.1054 -9.5985 13.9591
hospbi*age_gr*sample A 6 1 B 9 2 2.5052 2.3971 30 1.05 0.3043 Tukey-Kramer 1.0000 0.05 -2.3903 7.4007 -7.2269 12.2372
hospbi*age_gr*sample A 6 1 C 9 2 2.1320 2.5936 30 0.82 0.4176 Tukey-Kramer 1.0000 0.05 -3.1649 7.4288 -8.3979 12.6618
hospbi*age_gr*sample A 6 1 A 9 3 3.7321 1.5891 30 2.35 0.0256 Tukey-Kramer 0.8030 0.05 0.4868 6.9774 -2.7194 10.1836
hospbi*age_gr*sample A 6 1 B 9 3 3.7720 1.4803 30 2.55 0.0162 Tukey-Kramer 0.6845 0.05 0.7488 6.7951 -2.2379 9.7819
hospbi*age_gr*sample A 6 1 C 9 3 2.9783 1.5211 30 1.96 0.0596 Tukey-Kramer 0.9533 0.05 -0.1282 6.0849 -3.1974 9.1540
hospbi*age_gr*sample B 6 1 C 6 1 -1.0160 0.3885 30 -2.62 0.0138 Tukey-Kramer 0.6413 0.05 -1.8095 -0.2225 -2.5934 0.5614
hospbi*age_gr*sample B 6 1 A 6 2 2.5762 2.0934 30 1.23 0.2280 Tukey-Kramer 0.9999 0.05 -1.6992 6.8516 -5.9231 11.0754
hospbi*age_gr*sample B 6 1 B 6 2 3.0943 1.7455 30 1.77 0.0864 Tukey-Kramer 0.9832 0.05 -0.4706 6.6592 -3.9925 10.1811
hospbi*age_gr*sample B 6 1 C 6 2 1.8955 1.8808 30 1.01 0.3216 Tukey-Kramer 1.0000 0.05 -1.9455 5.7366 -5.7403 9.5313
hospbi*age_gr*sample B 6 1 A 6 3 3.0570 1.4063 30 2.17 0.0377 Tukey-Kramer 0.8858 0.05 0.1850 5.9290 -2.6524 8.7663
hospbi*age_gr*sample B 6 1 B 6 3 2.9153 1.2633 30 2.31 0.0281 Tukey-Kramer 0.8245 0.05 0.3352 5.4954 -2.2138 8.0444
hospbi*age_gr*sample B 6 1 C 6 3 2.2423 1.3176 30 1.70 0.0991 Tukey-Kramer 0.9894 0.05 -0.4486 4.9333 -3.1071 7.5918
hospbi*age_gr*sample B 6 1 A 9 1 1.4542 1.6429 30 0.89 0.3831 Tukey-Kramer 1.0000 0.05 -1.9010 4.8095 -5.2158 8.1243
hospbi*age_gr*sample B 6 1 B 9 1 1.6496 1.4252 30 1.16 0.2562 Tukey-Kramer 1.0000 0.05 -1.2611 4.5603 -4.1368 7.4359
hospbi*age_gr*sample B 6 1 C 9 1 0.9431 1.5088 30 0.63 0.5367 Tukey-Kramer 1.0000 0.05 -2.1383 4.0245 -5.1825 7.0687
hospbi*age_gr*sample B 6 1 A 9 2 1.4559 2.7838 30 0.52 0.6048 Tukey-Kramer 1.0000 0.05 -4.2293 7.1411 -9.8460 12.7578
hospbi*age_gr*sample B 6 1 B 9 2 1.7808 2.2535 30 0.79 0.4356 Tukey-Kramer 1.0000 0.05 -2.8215 6.3830 -7.3683 10.9298
hospbi*age_gr*sample B 6 1 C 9 2 1.4076 2.4615 30 0.57 0.5717 Tukey-Kramer 1.0000 0.05 -3.6195 6.4346 -8.5860 11.4011
hospbi*age_gr*sample B 6 1 A 9 3 3.0077 1.3628 30 2.21 0.0351 Tukey-Kramer 0.8719 0.05 0.2244 5.7910 -2.5254 8.5408
hospbi*age_gr*sample B 6 1 B 9 3 3.0476 1.2343 30 2.47 0.0195 Tukey-Kramer 0.7337 0.05 0.5268 5.5683 -1.9636 8.0587
hospbi*age_gr*sample B 6 1 C 9 3 2.2539 1.2830 30 1.76 0.0892 Tukey-Kramer 0.9848 0.05 -0.3663 4.8741 -2.9549 7.4628
hospbi*age_gr*sample C 6 1 A 6 2 3.5922 2.1512 30 1.67 0.1054 Tukey-Kramer 0.9916 0.05 -0.8011 7.9855 -5.1416 12.3259
hospbi*age_gr*sample C 6 1 B 6 2 4.1103 1.8144 30 2.27 0.0309 Tukey-Kramer 0.8454 0.05 0.4047 7.8158 -3.2562 11.4767
hospbi*age_gr*sample C 6 1 C 6 2 2.9115 1.9449 30 1.50 0.1448 Tukey-Kramer 0.9980 0.05 -1.0604 6.8835 -4.9845 10.8075
hospbi*age_gr*sample C 6 1 A 6 3 4.0730 1.4909 30 2.73 0.0104 Tukey-Kramer 0.5643 0.05 1.0281 7.1178 -1.9800 10.1259
hospbi*age_gr*sample C 6 1 B 6 3 3.9313 1.3569 30 2.90 0.0070 Tukey-Kramer 0.4575 0.05 1.1601 6.7025 -1.5777 9.4403
hospbi*age_gr*sample C 6 1 C 6 3 3.2583 1.4076 30 2.31 0.0276 Tukey-Kramer 0.8208 0.05 0.3837 6.1330 -2.4564 8.9731
hospbi*age_gr*sample C 6 1 A 9 1 2.4702 1.7159 30 1.44 0.1603 Tukey-Kramer 0.9988 0.05 -1.0341 5.9745 -4.4961 9.4366
hospbi*age_gr*sample C 6 1 B 9 1 2.6656 1.5088 30 1.77 0.0875 Tukey-Kramer 0.9838 0.05 -0.4158 5.7469 -3.4601 8.7912
hospbi*age_gr*sample C 6 1 C 9 1 1.9591 1.5880 30 1.23 0.2269 Tukey-Kramer 0.9999 0.05 -1.2840 5.2022 -4.4880 8.4062
hospbi*age_gr*sample C 6 1 A 9 2 2.4719 2.8275 30 0.87 0.3889 Tukey-Kramer 1.0000 0.05 -3.3025 8.2463 -9.0074 13.9512
hospbi*age_gr*sample C 6 1 B 9 2 2.7968 2.3072 30 1.21 0.2349 Tukey-Kramer 0.9999 0.05 -1.9153 7.5088 -6.5705 12.1641
hospbi*age_gr*sample C 6 1 C 9 2 2.4236 2.5108 30 0.97 0.3421 Tukey-Kramer 1.0000 0.05 -2.7042 7.5513 -7.7701 12.6173
hospbi*age_gr*sample C 6 1 A 9 3 4.0237 1.4500 30 2.77 0.0094 Tukey-Kramer 0.5360 0.05 1.0624 6.9850 -1.8632 9.9107
hospbi*age_gr*sample C 6 1 B 9 3 4.0636 1.3299 30 3.06 0.0047 Tukey-Kramer 0.3631 0.05 1.3476 6.7796 -1.3358 9.4629
hospbi*age_gr*sample C 6 1 C 9 3 3.2699 1.3752 30 2.38 0.0240 Tukey-Kramer 0.7870 0.05 0.4614 6.0785 -2.3134 8.8533
hospbi*age_gr*sample A 6 2 B 6 2 0.5181 0.6554 30 0.79 0.4355 Tukey-Kramer 1.0000 0.05 -0.8205 1.8567 -2.1430 3.1792
hospbi*age_gr*sample A 6 2 C 6 2 -0.6807 0.8678 30 -0.78 0.4390 Tukey-Kramer 1.0000 0.05 -2.4530 1.0917 -4.2040 2.8427
hospbi*age_gr*sample A 6 2 A 6 3 0.4808 2.0806 30 0.23 0.8188 Tukey-Kramer 1.0000 0.05 -3.7683 4.7299 -7.9662 8.9278
hospbi*age_gr*sample A 6 2 B 6 3 0.3391 1.9868 30 0.17 0.8656 Tukey-Kramer 1.0000 0.05 -3.7184 4.3966 -7.7270 8.4052
hospbi*age_gr*sample A 6 2 C 6 3 -0.3338 2.0217 30 -0.17 0.8699 Tukey-Kramer 1.0000 0.05 -4.4627 3.7950 -8.5419 7.8742
hospbi*age_gr*sample A 6 2 A 9 1 -1.1219 2.2473 30 -0.50 0.6212 Tukey-Kramer 1.0000 0.05 -5.7115 3.4676 -10.2458 8.0019
hospbi*age_gr*sample A 6 2 B 9 1 -0.9266 2.0934 30 -0.44 0.6612 Tukey-Kramer 1.0000 0.05 -5.2020 3.3488 -9.4259 7.5726
hospbi*age_gr*sample A 6 2 C 9 1 -1.6331 2.1512 30 -0.76 0.4537 Tukey-Kramer 1.0000 0.05 -6.0264 2.7603 -10.3668 7.1007
hospbi*age_gr*sample A 6 2 A 9 2 -1.1203 3.1781 30 -0.35 0.7269 Tukey-Kramer 1.0000 0.05 -7.6109 5.3703 -14.0233 11.7828
hospbi*age_gr*sample A 6 2 B 9 2 -0.7954 2.7257 30 -0.29 0.7724 Tukey-Kramer 1.0000 0.05 -6.3620 4.7712 -11.8616 10.2708
hospbi*age_gr*sample A 6 2 C 9 2 -1.1686 2.9000 30 -0.40 0.6898 Tukey-Kramer 1.0000 0.05 -7.0913 4.7540 -12.9426 10.6053
hospbi*age_gr*sample A 6 2 A 9 3 0.4315 2.0515 30 0.21 0.8348 Tukey-Kramer 1.0000 0.05 -3.7581 4.6212 -7.8973 8.7604
hospbi*age_gr*sample A 6 2 B 9 3 0.4714 1.9684 30 0.24 0.8124 Tukey-Kramer 1.0000 0.05 -3.5486 4.4914 -7.5203 8.4631
hospbi*age_gr*sample A 6 2 C 9 3 -0.3222 1.9993 30 -0.16 0.8730 Tukey-Kramer 1.0000 0.05 -4.4054 3.7609 -8.4393 7.7949
hospbi*age_gr*sample B 6 2 C 6 2 -1.1987 0.5495 30 -2.18 0.0371 Tukey-Kramer 0.8826 0.05 -2.3209 -0.07660 -3.4295 1.0320
hospbi*age_gr*sample B 6 2 A 6 3 -0.03732 1.7301 30 -0.02 0.9829 Tukey-Kramer 1.0000 0.05 -3.5706 3.4960 -7.0614 6.9868
hospbi*age_gr*sample B 6 2 B 6 3 -0.1790 1.6161 30 -0.11 0.9125 Tukey-Kramer 1.0000 0.05 -3.4794 3.1215 -6.7401 6.3821
hospbi*age_gr*sample B 6 2 C 6 3 -0.8519 1.6588 30 -0.51 0.6113 Tukey-Kramer 1.0000 0.05 -4.2397 2.5359 -7.5867 5.8829
hospbi*age_gr*sample B 6 2 A 9 1 -1.6400 1.9274 30 -0.85 0.4016 Tukey-Kramer 1.0000 0.05 -5.5762 2.2961 -9.4650 6.1849
hospbi*age_gr*sample B 6 2 B 9 1 -1.4447 1.7455 30 -0.83 0.4144 Tukey-Kramer 1.0000 0.05 -5.0096 2.1202 -8.5315 5.6421
hospbi*age_gr*sample B 6 2 C 9 1 -2.1512 1.8144 30 -1.19 0.2451 Tukey-Kramer 0.9999 0.05 -5.8567 1.5544 -9.5176 5.2153
hospbi*age_gr*sample B 6 2 A 9 2 -1.6384 2.9606 30 -0.55 0.5841 Tukey-Kramer 1.0000 0.05 -7.6847 4.4079 -13.6581 10.3814
hospbi*age_gr*sample B 6 2 B 9 2 -1.3135 2.4686 30 -0.53 0.5986 Tukey-Kramer 1.0000 0.05 -6.3550 3.7280 -11.3358 8.7088
hospbi*age_gr*sample B 6 2 C 9 2 -1.6867 2.6598 30 -0.63 0.5308 Tukey-Kramer 1.0000 0.05 -7.1188 3.7453 -12.4854 9.1119
hospbi*age_gr*sample B 6 2 A 9 3 -0.08656 1.6950 30 -0.05 0.9596 Tukey-Kramer 1.0000 0.05 -3.5482 3.3751 -6.9681 6.7950
hospbi*age_gr*sample B 6 2 B 9 3 -0.04670 1.5935 30 -0.03 0.9768 Tukey-Kramer 1.0000 0.05 -3.3010 3.2076 -6.5161 6.4227
hospbi*age_gr*sample B 6 2 C 9 3 -0.8403 1.6315 30 -0.52 0.6103 Tukey-Kramer 1.0000 0.05 -4.1722 2.4916 -7.4640 5.7833
hospbi*age_gr*sample C 6 2 A 6 3 1.1614 1.8664 30 0.62 0.5385 Tukey-Kramer 1.0000 0.05 -2.6503 4.9732 -6.4162 8.7391
hospbi*age_gr*sample C 6 2 B 6 3 1.0198 1.7613 30 0.58 0.5669 Tukey-Kramer 1.0000 0.05 -2.5772 4.6167 -6.1308 8.1703
hospbi*age_gr*sample C 6 2 C 6 3 0.3468 1.8006 30 0.19 0.8486 Tukey-Kramer 1.0000 0.05 -3.3305 4.0241 -6.9635 7.6571
hospbi*age_gr*sample C 6 2 A 9 1 -0.4413 2.0506 30 -0.22 0.8311 Tukey-Kramer 1.0000 0.05 -4.6292 3.7466 -8.7667 7.8841
hospbi*age_gr*sample C 6 2 B 9 1 -0.2460 1.8808 30 -0.13 0.8968 Tukey-Kramer 1.0000 0.05 -4.0870 3.5951 -7.8818 7.3898
hospbi*age_gr*sample C 6 2 C 9 1 -0.9524 1.9449 30 -0.49 0.6279 Tukey-Kramer 1.0000 0.05 -4.9244 3.0195 -8.8484 6.9436
hospbi*age_gr*sample C 6 2 A 9 2 -0.4396 3.0423 30 -0.14 0.8861 Tukey-Kramer 1.0000 0.05 -6.6527 5.7735 -12.7910 11.9118
hospbi*age_gr*sample C 6 2 B 9 2 -0.1148 2.5660 30 -0.04 0.9646 Tukey-Kramer 1.0000 0.05 -5.3552 5.1256 -10.5325 10.3029
hospbi*age_gr*sample C 6 2 C 9 2 -0.4880 2.7504 30 -0.18 0.8604 Tukey-Kramer 1.0000 0.05 -6.1051 5.1292 -11.6546 10.6787
hospbi*age_gr*sample C 6 2 A 9 3 1.1122 1.8339 30 0.61 0.5488 Tukey-Kramer 1.0000 0.05 -2.6332 4.8576 -6.3335 8.5579
hospbi*age_gr*sample C 6 2 B 9 3 1.1520 1.7405 30 0.66 0.5131 Tukey-Kramer 1.0000 0.05 -2.4026 4.7067 -5.9144 8.2185
hospbi*age_gr*sample C 6 2 C 9 3 0.3584 1.7754 30 0.20 0.8414 Tukey-Kramer 1.0000 0.05 -3.2674 3.9843 -6.8496 7.5664
hospbi*age_gr*sample A 6 3 B 6 3 -0.1417 0.3504 30 -0.40 0.6888 Tukey-Kramer 1.0000 0.05 -0.8572 0.5738 -1.5641 1.2807
hospbi*age_gr*sample A 6 3 C 6 3 -0.8146 0.4639 30 -1.76 0.0893 Tukey-Kramer 0.9848 0.05 -1.7620 0.1327 -2.6979 1.0687
hospbi*age_gr*sample A 6 3 A 9 1 -1.6027 1.6265 30 -0.99 0.3323 Tukey-Kramer 1.0000 0.05 -4.9244 1.7190 -8.2061 5.0006
hospbi*age_gr*sample A 6 3 B 9 1 -1.4074 1.4063 30 -1.00 0.3249 Tukey-Kramer 1.0000 0.05 -4.2794 1.4646 -7.1168 4.3020
hospbi*age_gr*sample A 6 3 C 9 1 -2.1139 1.4909 30 -1.42 0.1665 Tukey-Kramer 0.9991 0.05 -5.1587 0.9310 -8.1668 3.9391
hospbi*age_gr*sample A 6 3 A 9 2 -1.6011 2.7741 30 -0.58 0.5681 Tukey-Kramer 1.0000 0.05 -7.2665 4.0644 -12.8638 9.6616
hospbi*age_gr*sample A 6 3 B 9 2 -1.2762 2.2415 30 -0.57 0.5734 Tukey-Kramer 1.0000 0.05 -5.8540 3.3016 -10.3768 7.8244
hospbi*age_gr*sample A 6 3 C 9 2 -1.6494 2.4506 30 -0.67 0.5061 Tukey-Kramer 1.0000 0.05 -6.6541 3.3553 -11.5985 8.2997
hospbi*age_gr*sample A 6 3 A 9 3 -0.04924 1.3430 30 -0.04 0.9710 Tukey-Kramer 1.0000 0.05 -2.7920 2.6935 -5.5018 5.4033
hospbi*age_gr*sample A 6 3 B 9 3 -0.00938 1.2123 30 -0.01 0.9939 Tukey-Kramer 1.0000 0.05 -2.4853 2.4666 -4.9314 4.9127
hospbi*age_gr*sample A 6 3 C 9 3 -0.8030 1.2619 30 -0.64 0.5294 Tukey-Kramer 1.0000 0.05 -3.3801 1.7741 -5.9262 4.3202
hospbi*age_gr*sample B 6 3 C 6 3 -0.6730 0.2937 30 -2.29 0.0291 Tukey-Kramer 0.8327 0.05 -1.2728 -0.07314 -1.8654 0.5194
hospbi*age_gr*sample B 6 3 A 9 1 -1.4611 1.5046 30 -0.97 0.3393 Tukey-Kramer 1.0000 0.05 -4.5338 1.6117 -7.5696 4.6475
hospbi*age_gr*sample B 6 3 B 9 1 -1.2657 1.2633 30 -1.00 0.3244 Tukey-Kramer 1.0000 0.05 -3.8458 1.3143 -6.3948 3.8633
hospbi*age_gr*sample B 6 3 C 9 1 -1.9722 1.3569 30 -1.45 0.1565 Tukey-Kramer 0.9986 0.05 -4.7434 0.7990 -7.4811 3.5368
hospbi*age_gr*sample B 6 3 A 9 2 -1.4594 2.7044 30 -0.54 0.5934 Tukey-Kramer 1.0000 0.05 -6.9826 4.0638 -12.4393 9.5205
hospbi*age_gr*sample B 6 3 B 9 2 -1.1345 2.1547 30 -0.53 0.6024 Tukey-Kramer 1.0000 0.05 -5.5351 3.2661 -9.8827 7.6136
hospbi*age_gr*sample B 6 3 C 9 2 -1.5077 2.3714 30 -0.64 0.5297 Tukey-Kramer 1.0000 0.05 -6.3508 3.3354 -11.1356 8.1201
hospbi*age_gr*sample B 6 3 A 9 3 0.09242 1.1925 30 0.08 0.9387 Tukey-Kramer 1.0000 0.05 -2.3430 2.5279 -4.7491 4.9339
hospbi*age_gr*sample B 6 3 B 9 3 0.1323 1.0432 30 0.13 0.8999 Tukey-Kramer 1.0000 0.05 -1.9981 2.2627 -4.1029 4.3675
hospbi*age_gr*sample B 6 3 C 9 3 -0.6614 1.1004 30 -0.60 0.5523 Tukey-Kramer 1.0000 0.05 -2.9086 1.5859 -5.1287 3.8060
hospbi*age_gr*sample C 6 3 A 9 1 -0.7881 1.5504 30 -0.51 0.6150 Tukey-Kramer 1.0000 0.05 -3.9545 2.3783 -7.0828 5.5066
hospbi*age_gr*sample C 6 3 B 9 1 -0.5928 1.3176 30 -0.45 0.6560 Tukey-Kramer 1.0000 0.05 -3.2837 2.0982 -5.9422 4.7567
hospbi*age_gr*sample C 6 3 C 9 1 -1.2992 1.4076 30 -0.92 0.3634 Tukey-Kramer 1.0000 0.05 -4.1739 1.5754 -7.0139 4.4155
hospbi*age_gr*sample C 6 3 A 9 2 -0.7864 2.7302 30 -0.29 0.7753 Tukey-Kramer 1.0000 0.05 -6.3623 4.7894 -11.8710 10.2981
hospbi*age_gr*sample C 6 3 B 9 2 -0.4616 2.1870 30 -0.21 0.8343 Tukey-Kramer 1.0000 0.05 -4.9281 4.0049 -9.3408 8.4176
hospbi*age_gr*sample C 6 3 C 9 2 -0.8348 2.4008 30 -0.35 0.7305 Tukey-Kramer 1.0000 0.05 -5.7378 4.0683 -10.5818 8.9123
hospbi*age_gr*sample C 6 3 A 9 3 0.7654 1.2499 30 0.61 0.5449 Tukey-Kramer 1.0000 0.05 -1.7872 3.3180 -4.3090 5.8398
hospbi*age_gr*sample C 6 3 B 9 3 0.8052 1.1083 30 0.73 0.4731 Tukey-Kramer 1.0000 0.05 -1.4582 3.0687 -3.6943 5.3048
hospbi*age_gr*sample C 6 3 C 9 3 0.01160 1.1623 30 0.01 0.9921 Tukey-Kramer 1.0000 0.05 -2.3621 2.3853 -4.7072 4.7304
hospbi*age_gr*sample A 9 1 B 9 1 0.1953 0.4635 30 0.42 0.6764 Tukey-Kramer 1.0000 0.05 -0.7512 1.1419 -1.6863 2.0770
hospbi*age_gr*sample A 9 1 C 9 1 -0.5111 0.6136 30 -0.83 0.4115 Tukey-Kramer 1.0000 0.05 -1.7644 0.7421 -3.0025 1.9802
hospbi*age_gr*sample A 9 1 A 9 2 0.001670 2.9012 30 0.00 0.9995 Tukey-Kramer 1.0000 0.05 -5.9234 5.9268 -11.7771 11.7805
hospbi*age_gr*sample A 9 1 B 9 2 0.3265 2.3971 30 0.14 0.8926 Tukey-Kramer 1.0000 0.05 -4.5690 5.2220 -9.4055 10.0585
hospbi*age_gr*sample A 9 1 C 9 2 -0.04668 2.5936 30 -0.02 0.9858 Tukey-Kramer 1.0000 0.05 -5.3435 5.2501 -10.5765 10.4831
hospbi*age_gr*sample A 9 1 A 9 3 1.5535 1.5891 30 0.98 0.3361 Tukey-Kramer 1.0000 0.05 -1.6918 4.7988 -4.8980 8.0050
hospbi*age_gr*sample A 9 1 B 9 3 1.5933 1.4803 30 1.08 0.2903 Tukey-Kramer 1.0000 0.05 -1.4298 4.6165 -4.4165 7.6032
hospbi*age_gr*sample A 9 1 C 9 3 0.7997 1.5211 30 0.53 0.6029 Tukey-Kramer 1.0000 0.05 -2.3069 3.9063 -5.3760 6.9754
hospbi*age_gr*sample B 9 1 C 9 1 -0.7065 0.3885 30 -1.82 0.0790 Tukey-Kramer 0.9778 0.05 -1.4999 0.08701 -2.2839 0.8709
hospbi*age_gr*sample B 9 1 A 9 2 -0.1937 2.7838 30 -0.07 0.9450 Tukey-Kramer 1.0000 0.05 -5.8789 5.4915 -11.4956 11.1083
hospbi*age_gr*sample B 9 1 B 9 2 0.1312 2.2535 30 0.06 0.9540 Tukey-Kramer 1.0000 0.05 -4.4710 4.7334 -9.0179 9.2802
hospbi*age_gr*sample B 9 1 C 9 2 -0.2420 2.4615 30 -0.10 0.9223 Tukey-Kramer 1.0000 0.05 -5.2690 4.7850 -10.2355 9.7515
hospbi*age_gr*sample B 9 1 A 9 3 1.3581 1.3628 30 1.00 0.3270 Tukey-Kramer 1.0000 0.05 -1.4252 4.1415 -4.1749 6.8912
hospbi*age_gr*sample B 9 1 B 9 3 1.3980 1.2343 30 1.13 0.2663 Tukey-Kramer 1.0000 0.05 -1.1227 3.9188 -3.6131 6.4092
hospbi*age_gr*sample B 9 1 C 9 3 0.6044 1.2830 30 0.47 0.6410 Tukey-Kramer 1.0000 0.05 -2.0158 3.2246 -4.6045 5.8132
hospbi*age_gr*sample C 9 1 A 9 2 0.5128 2.8275 30 0.18 0.8573 Tukey-Kramer 1.0000 0.05 -5.2616 6.2872 -10.9665 11.9921
hospbi*age_gr*sample C 9 1 B 9 2 0.8377 2.3072 30 0.36 0.7191 Tukey-Kramer 1.0000 0.05 -3.8744 5.5497 -8.5296 10.2050
hospbi*age_gr*sample C 9 1 C 9 2 0.4645 2.5108 30 0.18 0.8545 Tukey-Kramer 1.0000 0.05 -4.6633 5.5922 -9.7292 10.6582
hospbi*age_gr*sample C 9 1 A 9 3 2.0646 1.4500 30 1.42 0.1648 Tukey-Kramer 0.9990 0.05 -0.8967 5.0259 -3.8223 7.9516
hospbi*age_gr*sample C 9 1 B 9 3 2.1045 1.3299 30 1.58 0.1240 Tukey-Kramer 0.9957 0.05 -0.6115 4.8205 -3.2949 7.5038
hospbi*age_gr*sample C 9 1 C 9 3 1.3108 1.3752 30 0.95 0.3481 Tukey-Kramer 1.0000 0.05 -1.4977 4.1194 -4.2725 6.8942
hospbi*age_gr*sample A 9 2 B 9 2 0.3249 0.9269 30 0.35 0.7284 Tukey-Kramer 1.0000 0.05 -1.5682 2.2179 -3.4385 4.0882
hospbi*age_gr*sample A 9 2 C 9 2 -0.04835 1.2273 30 -0.04 0.9688 Tukey-Kramer 1.0000 0.05 -2.5548 2.4581 -5.0311 4.9344
hospbi*age_gr*sample A 9 2 A 9 3 1.5518 2.7523 30 0.56 0.5771 Tukey-Kramer 1.0000 0.05 -4.0692 7.1728 -9.6226 12.7262
hospbi*age_gr*sample A 9 2 B 9 3 1.5917 2.6910 30 0.59 0.5586 Tukey-Kramer 1.0000 0.05 -3.9041 7.0874 -9.3337 12.5170
hospbi*age_gr*sample A 9 2 C 9 3 0.7980 2.7137 30 0.29 0.7707 Tukey-Kramer 1.0000 0.05 -4.7441 6.3401 -10.2194 11.8154
hospbi*age_gr*sample B 9 2 C 9 2 -0.3732 0.7771 30 -0.48 0.6345 Tukey-Kramer 1.0000 0.05 -1.9602 1.2137 -3.5280 2.7816
hospbi*age_gr*sample B 9 2 A 9 3 1.2270 2.2146 30 0.55 0.5837 Tukey-Kramer 1.0000 0.05 -3.2958 5.7497 -7.7641 10.2180
hospbi*age_gr*sample B 9 2 B 9 3 1.2668 2.1378 30 0.59 0.5579 Tukey-Kramer 1.0000 0.05 -3.0992 5.6329 -7.4127 9.9464
hospbi*age_gr*sample B 9 2 C 9 3 0.4732 2.1663 30 0.22 0.8286 Tukey-Kramer 1.0000 0.05 -3.9511 4.8974 -8.3220 9.2684
hospbi*age_gr*sample C 9 2 A 9 3 1.6002 2.4259 30 0.66 0.5145 Tukey-Kramer 1.0000 0.05 -3.3542 6.5545 -8.2489 11.4492
hospbi*age_gr*sample C 9 2 B 9 3 1.6400 2.3561 30 0.70 0.4917 Tukey-Kramer 1.0000 0.05 -3.1717 6.4518 -7.9255 11.2056
hospbi*age_gr*sample C 9 2 C 9 3 0.8464 2.3819 30 0.36 0.7248 Tukey-Kramer 1.0000 0.05 -4.0182 5.7110 -8.8242 10.5170
hospbi*age_gr*sample A 9 3 B 9 3 0.03987 0.3277 30 0.12 0.9040 Tukey-Kramer 1.0000 0.05 -0.6294 0.7092 -1.2907 1.3704
hospbi*age_gr*sample A 9 3 C 9 3 -0.7538 0.4339 30 -1.74 0.0926 Tukey-Kramer 0.9866 0.05 -1.6399 0.1324 -2.5154 1.0079
hospbi*age_gr*sample B 9 3 C 9 3 -0.7936 0.2747 30 -2.89 0.0071 Tukey-Kramer 0.4628 0.05 -1.3547 -0.2326 -1.9090 0.3217

Data for supplemental table 2 and Figure 1

In [19]:
/*ls means values by head body and tail*/

DATA insulin1_lsmeans1 (drop=age_group);
     set insulin1_means;
     if age_group^="" then delete;
     stain="Insulin           ";
     rename _NAME_=pancreas_region;
run;

PROC print data=insulin1_lsmeans1;
run;

/*grand mean values*/

PROC means data=insulin1_lsmeans1 mean;
     var lsmean;
     class hospbin;
     output out=insulin1_grandmean;
run;

DATA insulin1_grandmean (drop=_type_ _freq_ _stat_);
     set insulin1_grandmean;
     if _stat_^="MEAN" then delete;
     if hospbin="" then delete;
     pancreas_region="Overall";
     stain="Insulin           ";
run;

/*combine files into 1*/

DATA insulin1_fig1;
     set insulin1_lsmeans1 insulin1_grandmean;
run;

PROC print data=insulin1_fig1;
run;
Out[19]:
SAS Output
Obs pancreas_region hospbin LSMEAN stain
1 Head 3 3.67605 Insulin
2 Head 6 2.59539 Insulin
3 Head 9 2.25901 Insulin
4 Body 3 2.97310 Insulin
5 Body 6 2.22844 Insulin
6 Body 9 2.07233 Insulin
7 Tail 3 3.54317 Insulin
8 Tail 6 3.19101 Insulin
9 Tail 9 2.69677 Insulin

The MEANS Procedure

Analysis Variable : LSMEAN
hospbin N Obs Mean
3 3 3.3974434
6 3 2.6716118
9 3 2.3427013

Obs pancreas_region hospbin LSMEAN stain
1 Head 3 3.67605 Insulin
2 Head 6 2.59539 Insulin
3 Head 9 2.25901 Insulin
4 Body 3 2.97310 Insulin
5 Body 6 2.22844 Insulin
6 Body 9 2.07233 Insulin
7 Tail 3 3.54317 Insulin
8 Tail 6 3.19101 Insulin
9 Tail 9 2.69677 Insulin
10 Overall 3 3.39744 Insulin
11 Overall 6 2.67161 Insulin
12 Overall 9 2.34270 Insulin

Ki67 alone dataset

statistical analysis model

In [20]:
PROC glm data=ki67_no_insulin;
     class hospbin age_group;
     model Head Body Tail= hospbin|age_group/nouni; 
     repeated sample_type2 / short printe; 
     lsmeans hospbin|age_group /out=ki67_lsmeans (drop=stderr);
run;
quit;

PROC mixed data=ki67;
     class case hospbin age_group sample_type2;
     model percent_ki67=hospbin|age_group|sample_type2;
     repeated sample_type2/ subject=case(hospbin) type=un;
     lsmeans hospbin|age_group|sample_type2 /adjust=tukey cl pdiff alpha=0.05;
run;
Out[20]:
SAS Output

The GLM Procedure

Class Level Information
Class Levels Values
hospbin 3 3 6 9
age_group 3 1 2 3
Number of Observations Read 39
Number of Observations Used 39

The GLM Procedure

Repeated Measures Analysis of Variance

Repeated Measures Level Information
Dependent Variable Head Body Tail
Level of sample_type2 1 2 3
Partial Correlation Coefficients from the Error SSCP Matrix / Prob > |r|
DF = 30 Head Body Tail
Head
1.000000
 
0.988528
<.0001
0.976199
<.0001
Body
0.988528
<.0001
1.000000
 
0.985476
<.0001
Tail
0.976199
<.0001
0.985476
<.0001
1.000000
 
E = Error SSCP Matrix

sample_type2_N represents the contrast between the nth level of sample_type2 and the last
  sample_type2_1 sample_type2_2
sample_type2_1 17.476 12.541
sample_type2_2 12.541 12.249
Partial Correlation Coefficients from the Error SSCP Matrix of the Variables Defined by the Specified Transformation / Prob > |r|
DF = 30 sample_type2_1 sample_type2_2
sample_type2_1
1.000000
 
0.857138
<.0001
sample_type2_2
0.857138
<.0001
1.000000
 
Sphericity Tests
Variables DF Mauchly's Criterion Chi-Square Pr > ChiSq
Transformed Variates 2 0.2571104 39.389237 <.0001
Orthogonal Components 2 0.57698 15.948484 0.0003
MANOVA Test Criteria and Exact F Statistics for the Hypothesis of no sample_type2 Effect
H = Type III SSCP Matrix for sample_type2
E = Error SSCP Matrix

S=1 M=0 N=13.5
Statistic Value F Value Num DF Den DF Pr > F
Wilks' Lambda 0.91399941 1.36 2 29 0.2715
Pillai's Trace 0.08600059 1.36 2 29 0.2715
Hotelling-Lawley Trace 0.09409261 1.36 2 29 0.2715
Roy's Greatest Root 0.09409261 1.36 2 29 0.2715
MANOVA Test Criteria and F Approximations for the Hypothesis of no sample_type2*hospbin Effect
H = Type III SSCP Matrix for sample_type2*hospbin
E = Error SSCP Matrix

S=2 M=-0.5 N=13.5
Statistic Value F Value Num DF Den DF Pr > F
NOTE: F Statistic for Roy's Greatest Root is an upper bound.
NOTE: F Statistic for Wilks' Lambda is exact.
Wilks' Lambda 0.85190879 1.21 4 58 0.3165
Pillai's Trace 0.15021494 1.22 4 60 0.3126
Hotelling-Lawley Trace 0.17134169 1.23 4 33.787 0.3169
Roy's Greatest Root 0.15528831 2.33 2 30 0.1147
MANOVA Test Criteria and F Approximations for the Hypothesis of no sample_type2*age_group Effect
H = Type III SSCP Matrix for sample_type2*age_group
E = Error SSCP Matrix

S=2 M=-0.5 N=13.5
Statistic Value F Value Num DF Den DF Pr > F
NOTE: F Statistic for Roy's Greatest Root is an upper bound.
NOTE: F Statistic for Wilks' Lambda is exact.
Wilks' Lambda 0.72555649 2.52 4 58 0.0506
Pillai's Trace 0.27597287 2.40 4 60 0.0598
Hotelling-Lawley Trace 0.37614460 2.70 4 33.787 0.0471
Roy's Greatest Root 0.37045472 5.56 2 30 0.0089
MANOVA Test Criteria and F Approximations for the Hypothesis of no sample_type2*hospbin*age_group Effect
H = Type III SSCP Matrix for sample_type2*hospbin*age_group
E = Error SSCP Matrix

S=2 M=0.5 N=13.5
Statistic Value F Value Num DF Den DF Pr > F
NOTE: F Statistic for Roy's Greatest Root is an upper bound.
NOTE: F Statistic for Wilks' Lambda is exact.
Wilks' Lambda 0.83490934 0.68 8 58 0.7033
Pillai's Trace 0.17130447 0.70 8 60 0.6880
Hotelling-Lawley Trace 0.19029234 0.68 8 39.176 0.7088
Roy's Greatest Root 0.13527465 1.01 4 30 0.4156

The GLM Procedure

Repeated Measures Analysis of Variance

Tests of Hypotheses for Between Subjects Effects

Source DF Type III SS Mean Square F Value Pr > F
hospbin 2 20.6038257 10.3019129 0.61 0.5479
age_group 2 104.0057032 52.0028516 3.10 0.0598
hospbin*age_group 4 27.5292450 6.8823113 0.41 0.7999
Error 30 503.3919330 16.7797311    

The GLM Procedure

Repeated Measures Analysis of Variance

Univariate Tests of Hypotheses for Within Subject Effects

Source DF Type III SS Mean Square F Value Pr > F Adj Pr > F
G - G H-F-L
sample_type2 2 0.42096531 0.21048265 1.10 0.3387 0.3221 0.3239
sample_type2*hospbin 4 0.55942363 0.13985591 0.73 0.5734 0.5302 0.5343
sample_type2*age_group 4 2.65103233 0.66275808 3.47 0.0129 0.0266 0.0251
sample_type2*hospbin*age_group 8 1.10047484 0.13755935 0.72 0.6727 0.6269 0.6312
Error(sample_type2) 60 11.45605858 0.19093431        
Greenhouse-Geisser Epsilon 0.7027
Huynh-Feldt-Lecoutre Epsilon 0.7269

The GLM Procedure

Least Squares Means

hospbin Head LSMEAN
3 1.48994944
6 0.50260402
9 1.93661615
Plot of Head least-squares means for hospbin.
hospbin Body LSMEAN
3 1.70601904
6 0.67178747
9 1.75011958
Plot of Body least-squares means for hospbin.
hospbin Tail LSMEAN
3 1.41474194
6 0.58657634
9 1.58369347
Plot of Tail least-squares means for hospbin.
age_group Head LSMEAN
1 2.91283093
2 0.36615967
3 0.65017901
Plot of Head least-squares means for age_group.
age_group Body LSMEAN
1 3.00317592
2 0.46956717
3 0.65518300
Plot of Body least-squares means for age_group.
age_group Tail LSMEAN
1 2.35579814
2 0.45609933
3 0.77311427
Plot of Tail least-squares means for age_group.
hospbin age_group Head LSMEAN
3 1 3.60553700
3 2 0.61312600
3 3 0.25118531
6 1 1.01132305
6 2 0.19644000
6 3 0.30004900
9 1 4.12163275
9 2 0.28891300
9 3 1.39930271
Plot of Head least-squares means for hospbin*age_group.
hospbin age_group Body LSMEAN
3 1 3.85860700
3 2 1.00373250
3 3 0.25571763
6 1 1.37444750
6 2 0.16978500
6 3 0.47112991
9 1 3.77647325
9 2 0.23518400
9 3 1.23870148
Plot of Body least-squares means for hospbin*age_group.
hospbin age_group Tail LSMEAN
3 1 3.07558667
3 2 0.85218850
3 3 0.31645065
6 1 1.01652575
6 2 0.29059350
6 3 0.45260976
9 1 2.97528200
9 2 0.22551600
9 3 1.55028241
Plot of Tail least-squares means for hospbin*age_group.

The Mixed Procedure

Model Information
Data Set WORK.KI67
Dependent Variable percent_ki67
Covariance Structure Unstructured
Subject Effect Case(hospbin)
Estimation Method REML
Residual Variance Method None
Fixed Effects SE Method Model-Based
Degrees of Freedom Method Between-Within
Class Level Information
Class Levels Values
Case 39 6003 6005 6007 6008 6011 6019 6047 6048 6057 6060 6073 6099 6104 6106 6115 6117 6126 6129 6131 6134 6140 6144 6162 6165 6172 6174 6178 6179 6187 6200 6219 6229 6230 6235 6250 6251 6254 6278 6279
hospbin 3 3 6 9
age_group 3 1 2 3
sample_type2 3 A B C
Dimensions
Covariance Parameters 6
Columns in X 64
Columns in Z 0
Subjects 39
Max Obs per Subject 3
Number of Observations
Number of Observations Read 117
Number of Observations Used 117
Number of Observations Not Used 0
Iteration History
Iteration Evaluations -2 Res Log Like Criterion
0 1 446.46138402  
1 1 224.30343883 0.00000000
Convergence criteria met.
Covariance Parameter Estimates
Cov Parm Subject Estimate
UN(1,1) Case(hospbin) 6.7230
UN(2,1) Case(hospbin) 6.4731
UN(2,2) Case(hospbin) 6.3780
UN(3,1) Case(hospbin) 5.1006
UN(3,2) Case(hospbin) 5.0152
UN(3,3) Case(hospbin) 4.0607
Fit Statistics
-2 Res Log Likelihood 224.3
AIC (Smaller is Better) 236.3
AICC (Smaller is Better) 237.3
BIC (Smaller is Better) 246.3
Null Model Likelihood Ratio Test
DF Chi-Square Pr > ChiSq
5 222.16 <.0001
Type 3 Tests of Fixed Effects
Effect Num DF Den DF F Value Pr > F
hospbin 2 30 0.61 0.5479
age_group 2 30 3.10 0.0598
hospbin*age_group 4 30 0.41 0.7999
sample_type2 2 30 1.41 0.2595
hospbin*sample_type2 4 30 1.29 0.2979
age_group*sample_typ 4 30 2.82 0.0424
hospbi*age_gr*sample 8 30 0.71 0.6777
Least Squares Means
Effect sample_type2 hospbin age_group Estimate Standard
Error
DF t Value Pr > |t| Alpha Lower Upper
hospbin   3   1.5369 0.7717 30 1.99 0.0556 0.05 -0.03919 3.1130
hospbin   6   0.5870 0.7449 30 0.79 0.4369 0.05 -0.9343 2.1083
hospbin   9   1.7568 0.9244 30 1.90 0.0670 0.05 -0.1311 3.6447
age_group     1 2.7573 0.7196 30 3.83 0.0006 0.05 1.2876 4.2270
age_group     2 0.4306 1.1149 30 0.39 0.7020 0.05 -1.8463 2.7075
age_group     3 0.6928 0.4941 30 1.40 0.1711 0.05 -0.3163 1.7019
hospbin*age_group   3 1 3.5132 1.3654 30 2.57 0.0153 0.05 0.7247 6.3018
hospbin*age_group   3 2 0.8230 1.6723 30 0.49 0.6262 0.05 -2.5923 4.2383
hospbin*age_group   3 3 0.2745 0.8362 30 0.33 0.7450 0.05 -1.4332 1.9821
hospbin*age_group   6 1 1.1341 1.1825 30 0.96 0.3452 0.05 -1.2809 3.5491
hospbin*age_group   6 2 0.2189 1.6723 30 0.13 0.8967 0.05 -3.1964 3.6343
hospbin*age_group   6 3 0.4079 0.8939 30 0.46 0.6514 0.05 -1.4176 2.2335
hospbin*age_group   9 1 3.6245 1.1825 30 3.07 0.0046 0.05 1.2095 6.0395
hospbin*age_group   9 2 0.2499 2.3650 30 0.11 0.9166 0.05 -4.5801 5.0799
hospbin*age_group   9 3 1.3961 0.8362 30 1.67 0.1054 0.05 -0.3116 3.1038
sample_type2 A     1.3097 0.5175 30 2.53 0.0169 0.05 0.2529 2.3665
sample_type2 B     1.3760 0.5040 30 2.73 0.0105 0.05 0.3466 2.4053
sample_type2 C     1.1950 0.4022 30 2.97 0.0058 0.05 0.3737 2.0163
hospbin*sample_type2 A 3   1.4899 0.8461 30 1.76 0.0884 0.05 -0.2380 3.2179
hospbin*sample_type2 B 3   1.7060 0.8241 30 2.07 0.0471 0.05 0.02299 3.3890
hospbin*sample_type2 C 3   1.4147 0.6576 30 2.15 0.0396 0.05 0.07183 2.7577
hospbin*sample_type2 A 6   0.5026 0.8167 30 0.62 0.5429 0.05 -1.1653 2.1705
hospbin*sample_type2 B 6   0.6718 0.7954 30 0.84 0.4051 0.05 -0.9527 2.2963
hospbin*sample_type2 C 6   0.5866 0.6347 30 0.92 0.3628 0.05 -0.7097 1.8828
hospbin*sample_type2 A 9   1.9366 1.0135 30 1.91 0.0656 0.05 -0.1332 4.0064
hospbin*sample_type2 B 9   1.7501 0.9871 30 1.77 0.0864 0.05 -0.2659 3.7661
hospbin*sample_type2 C 9   1.5837 0.7876 30 2.01 0.0534 0.05 -0.02488 3.1923
age_group*sample_typ A   1 2.9128 0.7890 30 3.69 0.0009 0.05 1.3015 4.5242
age_group*sample_typ B   1 3.0032 0.7685 30 3.91 0.0005 0.05 1.4337 4.5726
age_group*sample_typ C   1 2.3558 0.6132 30 3.84 0.0006 0.05 1.1035 3.6081
age_group*sample_typ A   2 0.3662 1.2223 30 0.30 0.7666 0.05 -2.1301 2.8624
age_group*sample_typ B   2 0.4696 1.1905 30 0.39 0.6961 0.05 -1.9618 2.9009
age_group*sample_typ C   2 0.4561 0.9499 30 0.48 0.6346 0.05 -1.4839 2.3961
age_group*sample_typ A   3 0.6502 0.5417 30 1.20 0.2395 0.05 -0.4562 1.7565
age_group*sample_typ B   3 0.6552 0.5276 30 1.24 0.2240 0.05 -0.4224 1.7328
age_group*sample_typ C   3 0.7731 0.4210 30 1.84 0.0762 0.05 -0.08671 1.6329
hospbi*age_gr*sample A 3 1 3.6055 1.4970 30 2.41 0.0224 0.05 0.5483 6.6628
hospbi*age_gr*sample B 3 1 3.8586 1.4581 30 2.65 0.0128 0.05 0.8808 6.8364
hospbi*age_gr*sample C 3 1 3.0756 1.1634 30 2.64 0.0129 0.05 0.6996 5.4516
hospbi*age_gr*sample A 3 2 0.6131 1.8334 30 0.33 0.7404 0.05 -3.1313 4.3575
hospbi*age_gr*sample B 3 2 1.0037 1.7858 30 0.56 0.5782 0.05 -2.6433 4.6508
hospbi*age_gr*sample C 3 2 0.8522 1.4249 30 0.60 0.5543 0.05 -2.0578 3.7622
hospbi*age_gr*sample A 3 3 0.2512 0.9167 30 0.27 0.7860 0.05 -1.6210 2.1234
hospbi*age_gr*sample B 3 3 0.2557 0.8929 30 0.29 0.7765 0.05 -1.5678 2.0792
hospbi*age_gr*sample C 3 3 0.3165 0.7124 30 0.44 0.6601 0.05 -1.1386 1.7715
hospbi*age_gr*sample A 6 1 1.0113 1.2964 30 0.78 0.4415 0.05 -1.6364 3.6590
hospbi*age_gr*sample B 6 1 1.3744 1.2627 30 1.09 0.2851 0.05 -1.2044 3.9533
hospbi*age_gr*sample C 6 1 1.0165 1.0076 30 1.01 0.3211 0.05 -1.0412 3.0742
hospbi*age_gr*sample A 6 2 0.1964 1.8334 30 0.11 0.9154 0.05 -3.5479 3.9408
hospbi*age_gr*sample B 6 2 0.1698 1.7858 30 0.10 0.9249 0.05 -3.4772 3.8168
hospbi*age_gr*sample C 6 2 0.2906 1.4249 30 0.20 0.8398 0.05 -2.6194 3.2006
hospbi*age_gr*sample A 6 3 0.3000 0.9800 30 0.31 0.7616 0.05 -1.7014 2.3015
hospbi*age_gr*sample B 6 3 0.4711 0.9545 30 0.49 0.6252 0.05 -1.4783 2.4205
hospbi*age_gr*sample C 6 3 0.4526 0.7616 30 0.59 0.5568 0.05 -1.1029 2.0081
hospbi*age_gr*sample A 9 1 4.1216 1.2964 30 3.18 0.0034 0.05 1.4740 6.7693
hospbi*age_gr*sample B 9 1 3.7765 1.2627 30 2.99 0.0055 0.05 1.1976 6.3553
hospbi*age_gr*sample C 9 1 2.9753 1.0076 30 2.95 0.0061 0.05 0.9176 5.0330
hospbi*age_gr*sample A 9 2 0.2889 2.5929 30 0.11 0.9120 0.05 -5.0064 5.5843
hospbi*age_gr*sample B 9 2 0.2352 2.5255 30 0.09 0.9264 0.05 -4.9225 5.3929
hospbi*age_gr*sample C 9 2 0.2255 2.0151 30 0.11 0.9116 0.05 -3.8899 4.3409
hospbi*age_gr*sample A 9 3 1.3993 0.9167 30 1.53 0.1374 0.05 -0.4729 3.2715
hospbi*age_gr*sample B 9 3 1.2387 0.8929 30 1.39 0.1756 0.05 -0.5848 3.0622
hospbi*age_gr*sample C 9 3 1.5503 0.7124 30 2.18 0.0376 0.05 0.09527 3.0053
Differences of Least Squares Means
Effect sample_type2 hospbin age_group _sample_type2 hospbin _age_group Estimate Standard
Error
DF t Value Pr > |t| Adjustment Adj P Alpha Lower Upper Adj Lower Adj Upper
hospbin   3     6   0.9499 1.0726 30 0.89 0.3829 Tukey-Kramer 0.6534 0.05 -1.2406 3.1404 -1.6943 3.5941
hospbin   3     9   -0.2199 1.2042 30 -0.18 0.8563 Tukey-Kramer 0.9818 0.05 -2.6792 2.2394 -3.1886 2.7488
hospbin   6     9   -1.1698 1.1872 30 -0.99 0.3323 Tukey-Kramer 0.5916 0.05 -3.5944 1.2547 -4.0965 1.7569
age_group     1     2 2.3267 1.3270 30 1.75 0.0898 Tukey-Kramer 0.2026 0.05 -0.3834 5.0367 -0.9446 5.5980
age_group     1     3 2.0644 0.8730 30 2.36 0.0247 Tukey-Kramer 0.0621 0.05 0.2816 3.8472 -0.08760 4.2165
age_group     2     3 -0.2622 1.2195 30 -0.22 0.8312 Tukey-Kramer 0.9749 0.05 -2.7527 2.2283 -3.2685 2.7441
hospbin*age_group   3 1   3 2 2.6902 2.1589 30 1.25 0.2224 Tukey-Kramer 0.9389 0.05 -1.7189 7.0994 -4.5152 9.8957
hospbin*age_group   3 1   3 3 3.2388 1.6011 30 2.02 0.0521 Tukey-Kramer 0.5405 0.05 -0.03112 6.5087 -2.1049 8.5825
hospbin*age_group   3 1   6 1 2.3791 1.8063 30 1.32 0.1978 Tukey-Kramer 0.9182 0.05 -1.3098 6.0681 -3.6494 8.4077
hospbin*age_group   3 1   6 2 3.2943 2.1589 30 1.53 0.1375 Tukey-Kramer 0.8347 0.05 -1.1148 7.7035 -3.9112 10.4998
hospbin*age_group   3 1   6 3 3.1053 1.6320 30 1.90 0.0667 Tukey-Kramer 0.6171 0.05 -0.2277 6.4383 -2.3415 8.5521
hospbin*age_group   3 1   9 1 -0.1112 1.8063 30 -0.06 0.9513 Tukey-Kramer 1.0000 0.05 -3.8002 3.5777 -6.1398 5.9173
hospbin*age_group   3 1   9 2 3.2634 2.7309 30 1.19 0.2415 Tukey-Kramer 0.9514 0.05 -2.3138 8.8406 -5.8509 12.3777
hospbin*age_group   3 1   9 3 2.1171 1.6011 30 1.32 0.1961 Tukey-Kramer 0.9166 0.05 -1.1528 5.3871 -3.2266 7.4609
hospbin*age_group   3 2   3 3 0.5486 1.8697 30 0.29 0.7712 Tukey-Kramer 1.0000 0.05 -3.2699 4.3670 -5.6916 6.7887
hospbin*age_group   3 2   6 1 -0.3111 2.0482 30 -0.15 0.8803 Tukey-Kramer 1.0000 0.05 -4.4940 3.8718 -7.1468 6.5246
hospbin*age_group   3 2   6 2 0.6041 2.3650 30 0.26 0.8001 Tukey-Kramer 1.0000 0.05 -4.2259 5.4341 -7.2891 8.4973
hospbin*age_group   3 2   6 3 0.4151 1.8962 30 0.22 0.8282 Tukey-Kramer 1.0000 0.05 -3.4575 4.2877 -5.9136 6.7437
hospbin*age_group   3 2   9 1 -2.8014 2.0482 30 -1.37 0.1815 Tukey-Kramer 0.9011 0.05 -6.9843 1.3814 -9.6372 4.0343
hospbin*age_group   3 2   9 2 0.5731 2.8965 30 0.20 0.8445 Tukey-Kramer 1.0000 0.05 -5.3424 6.4886 -9.0940 10.2403
hospbin*age_group   3 2   9 3 -0.5731 1.8697 30 -0.31 0.7613 Tukey-Kramer 1.0000 0.05 -4.3915 3.2454 -6.8132 5.6670
hospbin*age_group   3 3   6 1 -0.8596 1.4483 30 -0.59 0.5572 Tukey-Kramer 0.9995 0.05 -3.8174 2.0981 -5.6932 3.9739
hospbin*age_group   3 3   6 2 0.05551 1.8697 30 0.03 0.9765 Tukey-Kramer 1.0000 0.05 -3.7629 3.8739 -6.1846 6.2956
hospbin*age_group   3 3   6 3 -0.1335 1.2240 30 -0.11 0.9139 Tukey-Kramer 1.0000 0.05 -2.6332 2.3663 -4.2186 3.9516
hospbin*age_group   3 3   9 1 -3.3500 1.4483 30 -2.31 0.0278 Tukey-Kramer 0.3661 0.05 -6.3078 -0.3923 -8.1836 1.4836
hospbin*age_group   3 3   9 2 0.02458 2.5085 30 0.01 0.9922 Tukey-Kramer 1.0000 0.05 -5.0984 5.1476 -8.3474 8.3966
hospbin*age_group   3 3   9 3 -1.1216 1.1825 30 -0.95 0.3504 Tukey-Kramer 0.9878 0.05 -3.5366 1.2933 -5.0682 2.8250
hospbin*age_group   6 1   6 2 0.9152 2.0482 30 0.45 0.6582 Tukey-Kramer 0.9999 0.05 -3.2677 5.0980 -5.9206 7.7509
hospbin*age_group   6 1   6 3 0.7262 1.4823 30 0.49 0.6278 Tukey-Kramer 0.9999 0.05 -2.3012 3.7535 -4.2212 5.6735
hospbin*age_group   6 1   9 1 -2.4904 1.6723 30 -1.49 0.1469 Tukey-Kramer 0.8517 0.05 -5.9057 0.9249 -8.0717 3.0910
hospbin*age_group   6 1   9 2 0.8842 2.6442 30 0.33 0.7404 Tukey-Kramer 1.0000 0.05 -4.5159 6.2843 -7.9406 9.7091
hospbin*age_group   6 1   9 3 -0.2620 1.4483 30 -0.18 0.8577 Tukey-Kramer 1.0000 0.05 -3.2197 2.6958 -5.0956 4.5716
hospbin*age_group   6 2   6 3 -0.1890 1.8962 30 -0.10 0.9213 Tukey-Kramer 1.0000 0.05 -4.0616 3.6836 -6.5176 6.1397
hospbin*age_group   6 2   9 1 -3.4055 2.0482 30 -1.66 0.1068 Tukey-Kramer 0.7631 0.05 -7.5884 0.7774 -10.2412 3.4302
hospbin*age_group   6 2   9 2 -0.03093 2.8965 30 -0.01 0.9916 Tukey-Kramer 1.0000 0.05 -5.9464 5.8846 -9.6981 9.6362
hospbin*age_group   6 2   9 3 -1.1772 1.8697 30 -0.63 0.5337 Tukey-Kramer 0.9993 0.05 -4.9956 2.6413 -7.4173 5.0630
hospbin*age_group   6 3   9 1 -3.2165 1.4823 30 -2.17 0.0381 Tukey-Kramer 0.4489 0.05 -6.2439 -0.1892 -8.1639 1.7308
hospbin*age_group   6 3   9 2 0.1581 2.5283 30 0.06 0.9506 Tukey-Kramer 1.0000 0.05 -5.0054 5.3215 -8.2801 8.5962
hospbin*age_group   6 3   9 3 -0.9882 1.2240 30 -0.81 0.4258 Tukey-Kramer 0.9958 0.05 -3.4879 1.5116 -5.0733 3.0970
hospbin*age_group   9 1   9 2 3.3746 2.6442 30 1.28 0.2117 Tukey-Kramer 0.9306 0.05 -2.0255 8.7747 -5.4503 12.1995
hospbin*age_group   9 1   9 3 2.2284 1.4483 30 1.54 0.1344 Tukey-Kramer 0.8285 0.05 -0.7294 5.1861 -2.6052 7.0619
hospbin*age_group   9 2   9 3 -1.1462 2.5085 30 -0.46 0.6510 Tukey-Kramer 0.9999 0.05 -6.2692 3.9767 -9.5182 7.2258
sample_type2 A     B     -0.06625 0.07852 30 -0.84 0.4055 Tukey-Kramer 0.6792 0.05 -0.2266 0.09410 -0.2598 0.1273
sample_type2 A     C     0.1147 0.1523 30 0.75 0.4572 Tukey-Kramer 0.7341 0.05 -0.1964 0.4258 -0.2608 0.4902
sample_type2 B     C     0.1810 0.1275 30 1.42 0.1662 Tukey-Kramer 0.3441 0.05 -0.07947 0.4414 -0.1334 0.4953
hospbin*sample_type2 A 3   B 3   -0.2161 0.1284 30 -1.68 0.1027 Tukey-Kramer 0.7516 0.05 -0.4783 0.04612 -0.6445 0.2124
hospbin*sample_type2 A 3   C 3   0.07521 0.2491 30 0.30 0.7648 Tukey-Kramer 1.0000 0.05 -0.4334 0.5838 -0.7560 0.9064
hospbin*sample_type2 A 3   A 6   0.9873 1.1759 30 0.84 0.4078 Tukey-Kramer 0.9945 0.05 -1.4142 3.3889 -2.9374 4.9120
hospbin*sample_type2 A 3   B 6   0.8182 1.1613 30 0.70 0.4865 Tukey-Kramer 0.9983 0.05 -1.5535 3.1898 -3.0577 4.6940
hospbin*sample_type2 A 3   C 6   0.9034 1.0577 30 0.85 0.3998 Tukey-Kramer 0.9938 0.05 -1.2567 3.0635 -2.6267 4.4334
hospbin*sample_type2 A 3   A 9   -0.4467 1.3202 30 -0.34 0.7375 Tukey-Kramer 1.0000 0.05 -3.1429 2.2496 -4.8529 3.9596
hospbin*sample_type2 A 3   B 9   -0.2602 1.3001 30 -0.20 0.8427 Tukey-Kramer 1.0000 0.05 -2.9153 2.3950 -4.5993 4.0789
hospbin*sample_type2 A 3   C 9   -0.09374 1.1560 30 -0.08 0.9359 Tukey-Kramer 1.0000 0.05 -2.4545 2.2670 -3.9518 3.7643
hospbin*sample_type2 B 3   C 3   0.2913 0.2085 30 1.40 0.1727 Tukey-Kramer 0.8902 0.05 -0.1346 0.7171 -0.4046 0.9872
hospbin*sample_type2 B 3   A 6   1.2034 1.1602 30 1.04 0.3079 Tukey-Kramer 0.9787 0.05 -1.1661 3.5729 -2.6688 5.0756
hospbin*sample_type2 B 3   B 6   1.0342 1.1454 30 0.90 0.3737 Tukey-Kramer 0.9911 0.05 -1.3049 3.3734 -2.7884 4.8569
hospbin*sample_type2 B 3   C 6   1.1194 1.0402 30 1.08 0.2904 Tukey-Kramer 0.9734 0.05 -1.0049 3.2438 -2.3522 4.5910
hospbin*sample_type2 B 3   A 9   -0.2306 1.3062 30 -0.18 0.8611 Tukey-Kramer 1.0000 0.05 -2.8983 2.4371 -4.5902 4.1290
hospbin*sample_type2 B 3   B 9   -0.04410 1.2859 30 -0.03 0.9729 Tukey-Kramer 1.0000 0.05 -2.6703 2.5821 -4.3358 4.2476
hospbin*sample_type2 B 3   C 9   0.1223 1.1400 30 0.11 0.9153 Tukey-Kramer 1.0000 0.05 -2.2058 2.4504 -3.6823 3.9269
hospbin*sample_type2 C 3   A 6   0.9121 1.0485 30 0.87 0.3912 Tukey-Kramer 0.9930 0.05 -1.2292 3.0535 -2.5872 4.4115
hospbin*sample_type2 C 3   B 6   0.7430 1.0320 30 0.72 0.4772 Tukey-Kramer 0.9981 0.05 -1.3648 2.8507 -2.7015 4.1874
hospbin*sample_type2 C 3   C 6   0.8282 0.9139 30 0.91 0.3721 Tukey-Kramer 0.9909 0.05 -1.0383 2.6946 -2.2220 3.8783
hospbin*sample_type2 C 3   A 9   -0.5219 1.2081 30 -0.43 0.6688 Tukey-Kramer 1.0000 0.05 -2.9891 1.9454 -4.5539 3.5102
hospbin*sample_type2 C 3   B 9   -0.3354 1.1861 30 -0.28 0.7793 Tukey-Kramer 1.0000 0.05 -2.7577 2.0869 -4.2939 3.6232
hospbin*sample_type2 C 3   C 9   -0.1690 1.0260 30 -0.16 0.8703 Tukey-Kramer 1.0000 0.05 -2.2644 1.9265 -3.5934 3.2555
hospbin*sample_type2 A 6   B 6   -0.1692 0.1239 30 -1.37 0.1823 Tukey-Kramer 0.9020 0.05 -0.4223 0.08389 -0.5828 0.2444
hospbin*sample_type2 A 6   C 6   -0.08397 0.2404 30 -0.35 0.7293 Tukey-Kramer 1.0000 0.05 -0.5749 0.4070 -0.8863 0.7184
hospbin*sample_type2 A 6   A 9   -1.4340 1.3016 30 -1.10 0.2793 Tukey-Kramer 0.9695 0.05 -4.0922 1.2242 -5.7780 2.9100
hospbin*sample_type2 A 6   B 9   -1.2475 1.2812 30 -0.97 0.3380 Tukey-Kramer 0.9856 0.05 -3.8640 1.3690 -5.5234 3.0284
hospbin*sample_type2 A 6   C 9   -1.0811 1.1346 30 -0.95 0.3483 Tukey-Kramer 0.9874 0.05 -3.3983 1.2361 -4.8679 2.7057
hospbin*sample_type2 B 6   C 6   0.08521 0.2013 30 0.42 0.6750 Tukey-Kramer 1.0000 0.05 -0.3258 0.4962 -0.5865 0.7569
hospbin*sample_type2 B 6   A 9   -1.2648 1.2884 30 -0.98 0.3341 Tukey-Kramer 0.9848 0.05 -3.8960 1.3663 -5.5647 3.0351
hospbin*sample_type2 B 6   B 9   -1.0783 1.2677 30 -0.85 0.4017 Tukey-Kramer 0.9940 0.05 -3.6674 1.5107 -5.3094 3.1527
hospbin*sample_type2 B 6   C 9   -0.9119 1.1194 30 -0.81 0.4217 Tukey-Kramer 0.9955 0.05 -3.1981 1.3743 -4.6480 2.8242
hospbin*sample_type2 C 6   A 9   -1.3500 1.1958 30 -1.13 0.2679 Tukey-Kramer 0.9648 0.05 -3.7922 1.0921 -5.3411 2.6410
hospbin*sample_type2 C 6   B 9   -1.1635 1.1736 30 -0.99 0.3294 Tukey-Kramer 0.9839 0.05 -3.5603 1.2332 -5.0803 2.7532
hospbin*sample_type2 C 6   C 9   -0.9971 1.0115 30 -0.99 0.3321 Tukey-Kramer 0.9844 0.05 -3.0630 1.0687 -4.3731 2.3789
hospbin*sample_type2 A 9   B 9   0.1865 0.1538 30 1.21 0.2347 Tukey-Kramer 0.9473 0.05 -0.1276 0.5006 -0.3267 0.6997
hospbin*sample_type2 A 9   C 9   0.3529 0.2983 30 1.18 0.2461 Tukey-Kramer 0.9541 0.05 -0.2563 0.9622 -0.6427 1.3486
hospbin*sample_type2 B 9   C 9   0.1664 0.2498 30 0.67 0.5103 Tukey-Kramer 0.9989 0.05 -0.3436 0.6765 -0.6671 1.0000
age_group*sample_typ A   1 B   1 -0.09034 0.1197 30 -0.75 0.4563 Tukey-Kramer 0.9973 0.05 -0.3348 0.1541 -0.4899 0.3092
age_group*sample_typ A   1 C   1 0.5570 0.2322 30 2.40 0.0229 Tukey-Kramer 0.3208 0.05 0.08272 1.0313 -0.2181 1.3322
age_group*sample_typ A   1 A   2 2.5467 1.4548 30 1.75 0.0903 Tukey-Kramer 0.7120 0.05 -0.4245 5.5178 -2.3088 7.4021
age_group*sample_typ A   1 B   2 2.4433 1.4282 30 1.71 0.0975 Tukey-Kramer 0.7356 0.05 -0.4736 5.3601 -2.3234 7.2100
age_group*sample_typ A   1 C   2 2.4567 1.2349 30 1.99 0.0558 Tukey-Kramer 0.5617 0.05 -0.06518 4.9786 -1.6646 6.5781
age_group*sample_typ A   1 A   3 2.2627 0.9571 30 2.36 0.0247 Tukey-Kramer 0.3386 0.05 0.3081 4.2172 -0.9315 5.4568
age_group*sample_typ A   1 B   3 2.2576 0.9492 30 2.38 0.0239 Tukey-Kramer 0.3311 0.05 0.3192 4.1961 -0.9102 5.4255
age_group*sample_typ A   1 C   3 2.1397 0.8943 30 2.39 0.0232 Tukey-Kramer 0.3238 0.05 0.3133 3.9661 -0.8450 5.1244
age_group*sample_typ B   1 C   1 0.6474 0.1944 30 3.33 0.0023 Tukey-Kramer 0.0509 0.05 0.2503 1.0445 -0.00155 1.2963
age_group*sample_typ B   1 A   2 2.6370 1.4438 30 1.83 0.0777 Tukey-Kramer 0.6653 0.05 -0.3116 5.5856 -2.1817 7.4557
age_group*sample_typ B   1 B   2 2.5336 1.4170 30 1.79 0.0839 Tukey-Kramer 0.6891 0.05 -0.3603 5.4275 -2.1956 7.2628
age_group*sample_typ B   1 C   2 2.5471 1.2219 30 2.08 0.0457 Tukey-Kramer 0.5015 0.05 0.05172 5.0424 -1.5309 6.6250
age_group*sample_typ B   1 A   3 2.3530 0.9402 30 2.50 0.0180 Tukey-Kramer 0.2704 0.05 0.4328 4.2732 -0.7850 5.4910
age_group*sample_typ B   1 B   3 2.3480 0.9322 30 2.52 0.0173 Tukey-Kramer 0.2631 0.05 0.4442 4.2518 -0.7631 5.4591
age_group*sample_typ B   1 C   3 2.2301 0.8762 30 2.55 0.0163 Tukey-Kramer 0.2515 0.05 0.4405 4.0196 -0.6944 5.1545
age_group*sample_typ C   1 A   2 1.9896 1.3675 30 1.45 0.1561 Tukey-Kramer 0.8668 0.05 -0.8031 4.7824 -2.5743 6.5536
age_group*sample_typ C   1 B   2 1.8862 1.3391 30 1.41 0.1693 Tukey-Kramer 0.8858 0.05 -0.8487 4.6211 -2.5832 6.3556
age_group*sample_typ C   1 C   2 1.8997 1.1306 30 1.68 0.1033 Tukey-Kramer 0.7532 0.05 -0.4094 4.2088 -1.8738 5.6732
age_group*sample_typ C   1 A   3 1.7056 0.8182 30 2.08 0.0457 Tukey-Kramer 0.5015 0.05 0.03463 3.3766 -1.0251 4.4364
age_group*sample_typ C   1 B   3 1.7006 0.8089 30 2.10 0.0440 Tukey-Kramer 0.4904 0.05 0.04853 3.3527 -0.9992 4.4005
age_group*sample_typ C   1 C   3 1.5827 0.7438 30 2.13 0.0417 Tukey-Kramer 0.4746 0.05 0.06364 3.1017 -0.8997 4.0651
age_group*sample_typ A   2 B   2 -0.1034 0.1855 30 -0.56 0.5813 Tukey-Kramer 0.9997 0.05 -0.4822 0.2754 -0.7224 0.5156
age_group*sample_typ A   2 C   2 -0.08994 0.3598 30 -0.25 0.8043 Tukey-Kramer 1.0000 0.05 -0.8247 0.6449 -1.2907 1.1109
age_group*sample_typ A   2 A   3 -0.2840 1.3370 30 -0.21 0.8332 Tukey-Kramer 1.0000 0.05 -3.0145 2.4464 -4.7461 4.1781
age_group*sample_typ A   2 B   3 -0.2890 1.3313 30 -0.22 0.8296 Tukey-Kramer 1.0000 0.05 -3.0079 2.4299 -4.7323 4.1542
age_group*sample_typ A   2 C   3 -0.4070 1.2928 30 -0.31 0.7551 Tukey-Kramer 1.0000 0.05 -3.0471 2.2332 -4.7216 3.9077
age_group*sample_typ B   2 C   2 0.01347 0.3012 30 0.04 0.9646 Tukey-Kramer 1.0000 0.05 -0.6017 0.6286 -0.9918 1.0188
age_group*sample_typ B   2 A   3 -0.1806 1.3080 30 -0.14 0.8911 Tukey-Kramer 1.0000 0.05 -2.8518 2.4906 -4.5460 4.1847
age_group*sample_typ B   2 B   3 -0.1856 1.3022 30 -0.14 0.8876 Tukey-Kramer 1.0000 0.05 -2.8451 2.4738 -4.5317 4.1605
age_group*sample_typ B   2 C   3 -0.3035 1.2628 30 -0.24 0.8117 Tukey-Kramer 1.0000 0.05 -2.8825 2.2754 -4.5180 3.9109
age_group*sample_typ C   2 A   3 -0.1941 1.0935 30 -0.18 0.8603 Tukey-Kramer 1.0000 0.05 -2.4274 2.0392 -3.8438 3.4556
age_group*sample_typ C   2 B   3 -0.1991 1.0866 30 -0.18 0.8559 Tukey-Kramer 1.0000 0.05 -2.4183 2.0201 -3.8257 3.4276
age_group*sample_typ C   2 C   3 -0.3170 1.0390 30 -0.31 0.7624 Tukey-Kramer 1.0000 0.05 -2.4390 1.8050 -3.7848 3.1508
age_group*sample_typ A   3 B   3 -0.00500 0.08220 30 -0.06 0.9519 Tukey-Kramer 1.0000 0.05 -0.1729 0.1629 -0.2793 0.2693
age_group*sample_typ A   3 C   3 -0.1229 0.1595 30 -0.77 0.4468 Tukey-Kramer 0.9969 0.05 -0.4486 0.2027 -0.6551 0.4093
age_group*sample_typ B   3 C   3 -0.1179 0.1335 30 -0.88 0.3841 Tukey-Kramer 0.9923 0.05 -0.3906 0.1547 -0.5635 0.3276
hospbi*age_gr*sample A 3 1 B 3 1 -0.2531 0.2271 30 -1.11 0.2741 Tukey-Kramer 1.0000 0.05 -0.7170 0.2108 -1.1753 0.6691
hospbi*age_gr*sample A 3 1 C 3 1 0.5300 0.4407 30 1.20 0.2385 Tukey-Kramer 0.9999 0.05 -0.3700 1.4299 -1.2591 2.3190
hospbi*age_gr*sample A 3 1 A 3 2 2.9924 2.3670 30 1.26 0.2159 Tukey-Kramer 0.9998 0.05 -1.8416 7.8264 -6.6173 12.6021
hospbi*age_gr*sample A 3 1 B 3 2 2.6018 2.3302 30 1.12 0.2731 Tukey-Kramer 1.0000 0.05 -2.1572 7.3608 -6.8588 12.0624
hospbi*age_gr*sample A 3 1 C 3 2 2.7533 2.0667 30 1.33 0.1928 Tukey-Kramer 0.9996 0.05 -1.4675 6.9742 -5.6374 11.1441
hospbi*age_gr*sample A 3 1 A 3 3 3.3544 1.7554 30 1.91 0.0656 Tukey-Kramer 0.9631 0.05 -0.2306 6.9393 -3.7724 10.4811
hospbi*age_gr*sample A 3 1 B 3 3 3.3498 1.7431 30 1.92 0.0642 Tukey-Kramer 0.9609 0.05 -0.2100 6.9096 -3.7269 10.4265
hospbi*age_gr*sample A 3 1 C 3 3 3.2891 1.6579 30 1.98 0.0565 Tukey-Kramer 0.9472 0.05 -0.09676 6.6749 -3.4418 10.0200
hospbi*age_gr*sample A 3 1 A 6 1 2.5942 1.9803 30 1.31 0.2001 Tukey-Kramer 0.9997 0.05 -1.4502 6.6386 -5.4459 10.6343
hospbi*age_gr*sample A 3 1 B 6 1 2.2311 1.9584 30 1.14 0.2636 Tukey-Kramer 1.0000 0.05 -1.7686 6.2308 -5.7201 10.1823
hospbi*age_gr*sample A 3 1 C 6 1 2.5890 1.8045 30 1.43 0.1617 Tukey-Kramer 0.9989 0.05 -1.0962 6.2743 -4.7371 9.9151
hospbi*age_gr*sample A 3 1 A 6 2 3.4091 2.3670 30 1.44 0.1601 Tukey-Kramer 0.9988 0.05 -1.4249 8.2431 -6.2006 13.0188
hospbi*age_gr*sample A 3 1 B 6 2 3.4358 2.3302 30 1.47 0.1508 Tukey-Kramer 0.9983 0.05 -1.3232 8.1947 -6.0249 12.8964
hospbi*age_gr*sample A 3 1 C 6 2 3.3149 2.0667 30 1.60 0.1192 Tukey-Kramer 0.9949 0.05 -0.9059 7.5357 -5.0758 11.7057
hospbi*age_gr*sample A 3 1 A 6 3 3.3055 1.7893 30 1.85 0.0746 Tukey-Kramer 0.9738 0.05 -0.3487 6.9596 -3.9588 10.5698
hospbi*age_gr*sample A 3 1 B 6 3 3.1344 1.7754 30 1.77 0.0877 Tukey-Kramer 0.9839 0.05 -0.4915 6.7603 -4.0737 10.3425
hospbi*age_gr*sample A 3 1 C 6 3 3.1529 1.6796 30 1.88 0.0702 Tukey-Kramer 0.9691 0.05 -0.2773 6.5831 -3.6662 9.9721
hospbi*age_gr*sample A 3 1 A 9 1 -0.5161 1.9803 30 -0.26 0.7962 Tukey-Kramer 1.0000 0.05 -4.5605 3.5283 -8.5562 7.5240
hospbi*age_gr*sample A 3 1 B 9 1 -0.1709 1.9584 30 -0.09 0.9310 Tukey-Kramer 1.0000 0.05 -4.1706 3.8287 -8.1221 7.7802
hospbi*age_gr*sample A 3 1 C 9 1 0.6303 1.8045 30 0.35 0.7293 Tukey-Kramer 1.0000 0.05 -3.0550 4.3155 -6.6959 7.9564
hospbi*age_gr*sample A 3 1 A 9 2 3.3166 2.9940 30 1.11 0.2768 Tukey-Kramer 1.0000 0.05 -2.7979 9.4312 -8.8388 15.4721
hospbi*age_gr*sample A 3 1 B 9 2 3.3704 2.9358 30 1.15 0.2600 Tukey-Kramer 1.0000 0.05 -2.6254 9.3661 -8.5489 15.2896
hospbi*age_gr*sample A 3 1 C 9 2 3.3800 2.5103 30 1.35 0.1882 Tukey-Kramer 0.9996 0.05 -1.7467 8.5068 -6.8117 13.5717
hospbi*age_gr*sample A 3 1 A 9 3 2.2062 1.7554 30 1.26 0.2185 Tukey-Kramer 0.9999 0.05 -1.3787 5.7912 -4.9205 9.3330
hospbi*age_gr*sample A 3 1 B 9 3 2.3668 1.7431 30 1.36 0.1846 Tukey-Kramer 0.9995 0.05 -1.1930 5.9266 -4.7099 9.4435
hospbi*age_gr*sample A 3 1 C 9 3 2.0553 1.6579 30 1.24 0.2247 Tukey-Kramer 0.9999 0.05 -1.3306 5.4411 -4.6757 8.7862
hospbi*age_gr*sample B 3 1 C 3 1 0.7830 0.3689 30 2.12 0.0422 Tukey-Kramer 0.9054 0.05 0.02960 1.5364 -0.7148 2.2808
hospbi*age_gr*sample B 3 1 A 3 2 3.2455 2.3425 30 1.39 0.1761 Tukey-Kramer 0.9993 0.05 -1.5386 8.0296 -6.2651 12.7561
hospbi*age_gr*sample B 3 1 B 3 2 2.8549 2.3054 30 1.24 0.2252 Tukey-Kramer 0.9999 0.05 -1.8534 7.5632 -6.5050 12.2148
hospbi*age_gr*sample B 3 1 C 3 2 3.0064 2.0387 30 1.47 0.1507 Tukey-Kramer 0.9983 0.05 -1.1572 7.1700 -5.2706 11.2834
hospbi*age_gr*sample B 3 1 A 3 3 3.6074 1.7223 30 2.09 0.0448 Tukey-Kramer 0.9151 0.05 0.08999 7.1249 -3.3851 10.5999
hospbi*age_gr*sample B 3 1 B 3 3 3.6029 1.7097 30 2.11 0.0436 Tukey-Kramer 0.9108 0.05 0.1111 7.0947 -3.3386 10.5444
hospbi*age_gr*sample B 3 1 C 3 3 3.5422 1.6228 30 2.18 0.0370 Tukey-Kramer 0.8822 0.05 0.2279 6.8564 -3.0464 10.1307
hospbi*age_gr*sample B 3 1 A 6 1 2.8473 1.9511 30 1.46 0.1549 Tukey-Kramer 0.9986 0.05 -1.1374 6.8319 -5.0740 10.7686
hospbi*age_gr*sample B 3 1 B 6 1 2.4842 1.9289 30 1.29 0.2076 Tukey-Kramer 0.9998 0.05 -1.4551 6.4234 -5.3469 10.3152
hospbi*age_gr*sample B 3 1 C 6 1 2.8421 1.7723 30 1.60 0.1193 Tukey-Kramer 0.9949 0.05 -0.7775 6.4617 -4.3535 10.0376
hospbi*age_gr*sample B 3 1 A 6 2 3.6622 2.3425 30 1.56 0.1285 Tukey-Kramer 0.9963 0.05 -1.1219 8.4463 -5.8484 13.1727
hospbi*age_gr*sample B 3 1 B 6 2 3.6888 2.3054 30 1.60 0.1201 Tukey-Kramer 0.9950 0.05 -1.0195 8.3971 -5.6711 13.0487
hospbi*age_gr*sample B 3 1 C 6 2 3.5680 2.0387 30 1.75 0.0903 Tukey-Kramer 0.9854 0.05 -0.5956 7.7316 -4.7090 11.8450
hospbi*age_gr*sample B 3 1 A 6 3 3.5586 1.7568 30 2.03 0.0518 Tukey-Kramer 0.9363 0.05 -0.02934 7.1465 -3.5740 10.6912
hospbi*age_gr*sample B 3 1 B 6 3 3.3875 1.7427 30 1.94 0.0614 Tukey-Kramer 0.9564 0.05 -0.1717 6.9466 -3.6879 10.4629
hospbi*age_gr*sample B 3 1 C 6 3 3.4060 1.6450 30 2.07 0.0471 Tukey-Kramer 0.9230 0.05 0.04643 6.7656 -3.2727 10.0847
hospbi*age_gr*sample B 3 1 A 9 1 -0.2630 1.9511 30 -0.13 0.8937 Tukey-Kramer 1.0000 0.05 -4.2477 3.7216 -8.1843 7.6583
hospbi*age_gr*sample B 3 1 B 9 1 0.08213 1.9289 30 0.04 0.9663 Tukey-Kramer 1.0000 0.05 -3.8571 4.0214 -7.7489 7.9132
hospbi*age_gr*sample B 3 1 C 9 1 0.8833 1.7723 30 0.50 0.6218 Tukey-Kramer 1.0000 0.05 -2.7363 4.5029 -6.3122 8.0789
hospbi*age_gr*sample B 3 1 A 9 2 3.5697 2.9747 30 1.20 0.2395 Tukey-Kramer 0.9999 0.05 -2.5055 9.6449 -8.5075 15.6469
hospbi*age_gr*sample B 3 1 B 9 2 3.6234 2.9162 30 1.24 0.2237 Tukey-Kramer 0.9999 0.05 -2.3322 9.5790 -8.2160 15.4628
hospbi*age_gr*sample B 3 1 C 9 2 3.6331 2.4873 30 1.46 0.1545 Tukey-Kramer 0.9985 0.05 -1.4466 8.7128 -6.4652 13.7314
hospbi*age_gr*sample B 3 1 A 9 3 2.4593 1.7223 30 1.43 0.1636 Tukey-Kramer 0.9990 0.05 -1.0581 5.9767 -4.5332 9.4518
hospbi*age_gr*sample B 3 1 B 9 3 2.6199 1.7097 30 1.53 0.1359 Tukey-Kramer 0.9972 0.05 -0.8719 6.1117 -4.3216 9.5614
hospbi*age_gr*sample B 3 1 C 9 3 2.3083 1.6228 30 1.42 0.1652 Tukey-Kramer 0.9990 0.05 -1.0059 5.6226 -4.2803 8.8969
hospbi*age_gr*sample C 3 1 A 3 2 2.4625 2.1714 30 1.13 0.2658 Tukey-Kramer 1.0000 0.05 -1.9722 6.8971 -6.3534 11.2783
hospbi*age_gr*sample C 3 1 B 3 2 2.0719 2.1313 30 0.97 0.3388 Tukey-Kramer 1.0000 0.05 -2.2809 6.4246 -6.5812 10.7249
hospbi*age_gr*sample C 3 1 C 3 2 2.2234 1.8395 30 1.21 0.2362 Tukey-Kramer 0.9999 0.05 -1.5334 5.9802 -5.2450 9.6918
hospbi*age_gr*sample C 3 1 A 3 3 2.8244 1.4812 30 1.91 0.0662 Tukey-Kramer 0.9638 0.05 -0.2006 5.8494 -3.1892 8.8380
hospbi*age_gr*sample C 3 1 B 3 3 2.8199 1.4666 30 1.92 0.0640 Tukey-Kramer 0.9607 0.05 -0.1752 5.8150 -3.1343 8.7740
hospbi*age_gr*sample C 3 1 C 3 3 2.7591 1.3642 30 2.02 0.0521 Tukey-Kramer 0.9372 0.05 -0.02700 5.5453 -2.7796 8.2979
hospbi*age_gr*sample C 3 1 A 6 1 2.0643 1.7419 30 1.19 0.2453 Tukey-Kramer 0.9999 0.05 -1.4932 5.6217 -5.0079 9.1364
hospbi*age_gr*sample C 3 1 B 6 1 1.7011 1.7170 30 0.99 0.3297 Tukey-Kramer 1.0000 0.05 -1.8054 5.2077 -5.2697 8.6720
hospbi*age_gr*sample C 3 1 C 6 1 2.0591 1.5391 30 1.34 0.1910 Tukey-Kramer 0.9996 0.05 -1.0841 5.2022 -4.1895 8.3076
hospbi*age_gr*sample C 3 1 A 6 2 2.8791 2.1714 30 1.33 0.1949 Tukey-Kramer 0.9997 0.05 -1.5555 7.3138 -5.9367 11.6950
hospbi*age_gr*sample C 3 1 B 6 2 2.9058 2.1313 30 1.36 0.1829 Tukey-Kramer 0.9995 0.05 -1.4469 7.2585 -5.7473 11.5589
hospbi*age_gr*sample C 3 1 C 6 2 2.7850 1.8395 30 1.51 0.1405 Tukey-Kramer 0.9976 0.05 -0.9718 6.5418 -4.6834 10.2534
hospbi*age_gr*sample C 3 1 A 6 3 2.7755 1.5212 30 1.82 0.0780 Tukey-Kramer 0.9770 0.05 -0.3311 5.8822 -3.4004 8.9514
hospbi*age_gr*sample C 3 1 B 6 3 2.6045 1.5049 30 1.73 0.0938 Tukey-Kramer 0.9872 0.05 -0.4689 5.6778 -3.5053 8.7142
hospbi*age_gr*sample C 3 1 C 6 3 2.6230 1.3906 30 1.89 0.0690 Tukey-Kramer 0.9675 0.05 -0.2169 5.4629 -3.0226 8.2686
hospbi*age_gr*sample C 3 1 A 9 1 -1.0460 1.7419 30 -0.60 0.5527 Tukey-Kramer 1.0000 0.05 -4.6035 2.5114 -8.1182 6.0261
hospbi*age_gr*sample C 3 1 B 9 1 -0.7009 1.7170 30 -0.41 0.6860 Tukey-Kramer 1.0000 0.05 -4.2074 2.8057 -7.6718 6.2700
hospbi*age_gr*sample C 3 1 C 9 1 0.1003 1.5391 30 0.07 0.9485 Tukey-Kramer 1.0000 0.05 -3.0429 3.2435 -6.1482 6.3488
hospbi*age_gr*sample C 3 1 A 9 2 2.7867 2.8419 30 0.98 0.3347 Tukey-Kramer 1.0000 0.05 -3.0173 8.5907 -8.7514 14.3247
hospbi*age_gr*sample C 3 1 B 9 2 2.8404 2.7806 30 1.02 0.3152 Tukey-Kramer 1.0000 0.05 -2.8383 8.5191 -8.4485 14.1293
hospbi*age_gr*sample C 3 1 C 9 2 2.8501 2.3268 30 1.22 0.2302 Tukey-Kramer 0.9999 0.05 -1.9020 7.6021 -6.5968 12.2969
hospbi*age_gr*sample C 3 1 A 9 3 1.6763 1.4812 30 1.13 0.2667 Tukey-Kramer 1.0000 0.05 -1.3487 4.7013 -4.3373 7.6898
hospbi*age_gr*sample C 3 1 B 9 3 1.8369 1.4666 30 1.25 0.2201 Tukey-Kramer 0.9999 0.05 -1.1582 4.8320 -4.1173 7.7910
hospbi*age_gr*sample C 3 1 C 9 3 1.5253 1.3642 30 1.12 0.2724 Tukey-Kramer 1.0000 0.05 -1.2608 4.3114 -4.0134 7.0640
hospbi*age_gr*sample A 3 2 B 3 2 -0.3906 0.2782 30 -1.40 0.1706 Tukey-Kramer 0.9992 0.05 -0.9588 0.1775 -1.5201 0.7389
hospbi*age_gr*sample A 3 2 C 3 2 -0.2391 0.5397 30 -0.44 0.6610 Tukey-Kramer 1.0000 0.05 -1.3413 0.8631 -2.4302 1.9520
hospbi*age_gr*sample A 3 2 A 3 3 0.3619 2.0498 30 0.18 0.8610 Tukey-Kramer 1.0000 0.05 -3.8244 4.5483 -7.9603 8.6842
hospbi*age_gr*sample A 3 2 B 3 3 0.3574 2.0393 30 0.18 0.8621 Tukey-Kramer 1.0000 0.05 -3.8074 4.5222 -7.9220 8.6369
hospbi*age_gr*sample A 3 2 C 3 3 0.2967 1.9670 30 0.15 0.8811 Tukey-Kramer 1.0000 0.05 -3.7205 4.3138 -7.6892 8.2826
hospbi*age_gr*sample A 3 2 A 6 1 -0.3982 2.2455 30 -0.18 0.8604 Tukey-Kramer 1.0000 0.05 -4.9841 4.1877 -9.5148 8.7184
hospbi*age_gr*sample A 3 2 B 6 1 -0.7613 2.2262 30 -0.34 0.7347 Tukey-Kramer 1.0000 0.05 -5.3078 3.7852 -9.7996 8.2770
hospbi*age_gr*sample A 3 2 C 6 1 -0.4034 2.0920 30 -0.19 0.8484 Tukey-Kramer 1.0000 0.05 -4.6759 3.8691 -8.8970 8.0902
hospbi*age_gr*sample A 3 2 A 6 2 0.4167 2.5929 30 0.16 0.8734 Tukey-Kramer 1.0000 0.05 -4.8787 5.7120 -10.1102 10.9436
hospbi*age_gr*sample A 3 2 B 6 2 0.4433 2.5594 30 0.17 0.8636 Tukey-Kramer 1.0000 0.05 -4.7836 5.6703 -9.9476 10.8343
hospbi*age_gr*sample A 3 2 C 6 2 0.3225 2.3220 30 0.14 0.8905 Tukey-Kramer 1.0000 0.05 -4.4197 5.0648 -9.1048 9.7499
hospbi*age_gr*sample A 3 2 A 6 3 0.3131 2.0789 30 0.15 0.8813 Tukey-Kramer 1.0000 0.05 -3.9327 4.5588 -8.1272 8.7534
hospbi*age_gr*sample A 3 2 B 6 3 0.1420 2.0670 30 0.07 0.9457 Tukey-Kramer 1.0000 0.05 -4.0795 4.3634 -8.2501 8.5340
hospbi*age_gr*sample A 3 2 C 6 3 0.1605 1.9853 30 0.08 0.9361 Tukey-Kramer 1.0000 0.05 -3.8941 4.2151 -7.8999 8.2209
hospbi*age_gr*sample A 3 2 A 9 1 -3.5085 2.2455 30 -1.56 0.1287 Tukey-Kramer 0.9964 0.05 -8.0944 1.0774 -12.6251 5.6081
hospbi*age_gr*sample A 3 2 B 9 1 -3.1633 2.2262 30 -1.42 0.1656 Tukey-Kramer 0.9990 0.05 -7.7099 1.3832 -12.2016 5.8749
hospbi*age_gr*sample A 3 2 C 9 1 -2.3622 2.0920 30 -1.13 0.2678 Tukey-Kramer 1.0000 0.05 -6.6347 1.9104 -10.8558 6.1314
hospbi*age_gr*sample A 3 2 A 9 2 0.3242 3.1756 30 0.10 0.9194 Tukey-Kramer 1.0000 0.05 -6.1612 6.8097 -12.5686 13.2170
hospbi*age_gr*sample A 3 2 B 9 2 0.3779 3.1208 30 0.12 0.9044 Tukey-Kramer 1.0000 0.05 -5.9956 6.7515 -12.2924 13.0483
hospbi*age_gr*sample A 3 2 C 9 2 0.3876 2.7244 30 0.14 0.8878 Tukey-Kramer 1.0000 0.05 -5.1763 5.9515 -10.6732 11.4484
hospbi*age_gr*sample A 3 2 A 9 3 -0.7862 2.0498 30 -0.38 0.7040 Tukey-Kramer 1.0000 0.05 -4.9725 3.4002 -9.1084 7.5361
hospbi*age_gr*sample A 3 2 B 9 3 -0.6256 2.0393 30 -0.31 0.7611 Tukey-Kramer 1.0000 0.05 -4.7904 3.5392 -8.9050 7.6539
hospbi*age_gr*sample A 3 2 C 9 3 -0.9372 1.9670 30 -0.48 0.6372 Tukey-Kramer 1.0000 0.05 -4.9543 3.0800 -8.9231 7.0487
hospbi*age_gr*sample B 3 2 C 3 2 0.1515 0.4518 30 0.34 0.7397 Tukey-Kramer 1.0000 0.05 -0.7712 1.0743 -1.6828 1.9859
hospbi*age_gr*sample B 3 2 A 3 3 0.7525 2.0073 30 0.37 0.7104 Tukey-Kramer 1.0000 0.05 -3.3470 4.8521 -7.3971 8.9022
hospbi*age_gr*sample B 3 2 B 3 3 0.7480 1.9966 30 0.37 0.7106 Tukey-Kramer 1.0000 0.05 -3.3295 4.8255 -7.3579 8.8539
hospbi*age_gr*sample B 3 2 C 3 3 0.6873 1.9226 30 0.36 0.7232 Tukey-Kramer 1.0000 0.05 -3.2393 4.6138 -7.1186 8.4931
hospbi*age_gr*sample B 3 2 A 6 1 -0.00759 2.2067 30 -0.00 0.9973 Tukey-Kramer 1.0000 0.05 -4.5144 4.4992 -8.9669 8.9517
hospbi*age_gr*sample B 3 2 B 6 1 -0.3707 2.1871 30 -0.17 0.8665 Tukey-Kramer 1.0000 0.05 -4.8374 4.0960 -9.2503 8.5089
hospbi*age_gr*sample B 3 2 C 6 1 -0.01279 2.0504 30 -0.01 0.9951 Tukey-Kramer 1.0000 0.05 -4.2003 4.1747 -8.3373 8.3117
hospbi*age_gr*sample B 3 2 A 6 2 0.8073 2.5594 30 0.32 0.7546 Tukey-Kramer 1.0000 0.05 -4.4197 6.0343 -9.5837 11.1983
hospbi*age_gr*sample B 3 2 B 6 2 0.8339 2.5255 30 0.33 0.7435 Tukey-Kramer 1.0000 0.05 -4.3237 5.9916 -9.4193 11.0872
hospbi*age_gr*sample B 3 2 C 6 2 0.7131 2.2846 30 0.31 0.7571 Tukey-Kramer 1.0000 0.05 -3.9526 5.3789 -8.5621 9.9884
hospbi*age_gr*sample B 3 2 A 6 3 0.7037 2.0370 30 0.35 0.7322 Tukey-Kramer 1.0000 0.05 -3.4564 4.8638 -7.5665 8.9738
hospbi*age_gr*sample B 3 2 B 6 3 0.5326 2.0249 30 0.26 0.7943 Tukey-Kramer 1.0000 0.05 -3.6027 4.6679 -7.6883 8.7535
hospbi*age_gr*sample B 3 2 C 6 3 0.5511 1.9414 30 0.28 0.7785 Tukey-Kramer 1.0000 0.05 -3.4138 4.5160 -7.3309 8.4331
hospbi*age_gr*sample B 3 2 A 9 1 -3.1179 2.2067 30 -1.41 0.1680 Tukey-Kramer 0.9991 0.05 -7.6247 1.3889 -12.0772 5.8414
hospbi*age_gr*sample B 3 2 B 9 1 -2.7727 2.1871 30 -1.27 0.2146 Tukey-Kramer 0.9998 0.05 -7.2394 1.6939 -11.6523 6.1068
hospbi*age_gr*sample B 3 2 C 9 1 -1.9715 2.0504 30 -0.96 0.3440 Tukey-Kramer 1.0000 0.05 -6.1590 2.2159 -10.2961 6.3530
hospbi*age_gr*sample B 3 2 A 9 2 0.7148 3.1483 30 0.23 0.8219 Tukey-Kramer 1.0000 0.05 -5.7149 7.1446 -12.0672 13.4969
hospbi*age_gr*sample B 3 2 B 9 2 0.7685 3.0930 30 0.25 0.8055 Tukey-Kramer 1.0000 0.05 -5.5483 7.0854 -11.7891 13.3262
hospbi*age_gr*sample B 3 2 C 9 2 0.7782 2.6925 30 0.29 0.7745 Tukey-Kramer 1.0000 0.05 -4.7206 6.2771 -10.1533 11.7097
hospbi*age_gr*sample B 3 2 A 9 3 -0.3956 2.0073 30 -0.20 0.8451 Tukey-Kramer 1.0000 0.05 -4.4951 3.7039 -8.5452 7.7541
hospbi*age_gr*sample B 3 2 B 9 3 -0.2350 1.9966 30 -0.12 0.9071 Tukey-Kramer 1.0000 0.05 -4.3125 3.8425 -8.3409 7.8709
hospbi*age_gr*sample B 3 2 C 9 3 -0.5465 1.9226 30 -0.28 0.7782 Tukey-Kramer 1.0000 0.05 -4.4731 3.3800 -8.3524 7.2593
hospbi*age_gr*sample C 3 2 A 3 3 0.6010 1.6943 30 0.35 0.7253 Tukey-Kramer 1.0000 0.05 -2.8592 4.0613 -6.2778 7.4798
hospbi*age_gr*sample C 3 2 B 3 3 0.5965 1.6815 30 0.35 0.7253 Tukey-Kramer 1.0000 0.05 -2.8377 4.0306 -6.2305 7.4234
hospbi*age_gr*sample C 3 2 C 3 3 0.5357 1.5931 30 0.34 0.7390 Tukey-Kramer 1.0000 0.05 -2.7178 3.7892 -5.9321 7.0036
hospbi*age_gr*sample C 3 2 A 6 1 -0.1591 1.9264 30 -0.08 0.9347 Tukey-Kramer 1.0000 0.05 -4.0934 3.7751 -7.9803 7.6620
hospbi*age_gr*sample C 3 2 B 6 1 -0.5223 1.9039 30 -0.27 0.7857 Tukey-Kramer 1.0000 0.05 -4.4105 3.3660 -8.2520 7.2075
hospbi*age_gr*sample C 3 2 C 6 1 -0.1643 1.7451 30 -0.09 0.9256 Tukey-Kramer 1.0000 0.05 -3.7284 3.3997 -7.2495 6.9208
hospbi*age_gr*sample C 3 2 A 6 2 0.6557 2.3220 30 0.28 0.7796 Tukey-Kramer 1.0000 0.05 -4.0865 5.3980 -8.7716 10.0831
hospbi*age_gr*sample C 3 2 B 6 2 0.6824 2.2846 30 0.30 0.7672 Tukey-Kramer 1.0000 0.05 -3.9833 5.3481 -8.5929 9.9577
hospbi*age_gr*sample C 3 2 C 6 2 0.5616 2.0151 30 0.28 0.7824 Tukey-Kramer 1.0000 0.05 -3.5538 4.6770 -7.6196 8.7428
hospbi*age_gr*sample C 3 2 A 6 3 0.5521 1.7294 30 0.32 0.7517 Tukey-Kramer 1.0000 0.05 -2.9797 4.0840 -6.4691 7.5733
hospbi*age_gr*sample C 3 2 B 6 3 0.3811 1.7151 30 0.22 0.8257 Tukey-Kramer 1.0000 0.05 -3.1216 3.8837 -6.5820 7.3442
hospbi*age_gr*sample C 3 2 C 6 3 0.3996 1.6157 30 0.25 0.8064 Tukey-Kramer 1.0000 0.05 -2.9001 3.6992 -6.1600 6.9592
hospbi*age_gr*sample C 3 2 A 9 1 -3.2694 1.9264 30 -1.70 0.1000 Tukey-Kramer 0.9898 0.05 -7.2037 0.6648 -11.0906 4.5517
hospbi*age_gr*sample C 3 2 B 9 1 -2.9243 1.9039 30 -1.54 0.1350 Tukey-Kramer 0.9971 0.05 -6.8126 0.9640 -10.6540 4.8054
hospbi*age_gr*sample C 3 2 C 9 1 -2.1231 1.7451 30 -1.22 0.2332 Tukey-Kramer 0.9999 0.05 -5.6871 1.4409 -9.2082 4.9621
hospbi*age_gr*sample C 3 2 A 9 2 0.5633 2.9586 30 0.19 0.8503 Tukey-Kramer 1.0000 0.05 -5.4790 6.6055 -11.4485 12.5750
hospbi*age_gr*sample C 3 2 B 9 2 0.6170 2.8997 30 0.21 0.8329 Tukey-Kramer 1.0000 0.05 -5.3050 6.5390 -11.1556 12.3897
hospbi*age_gr*sample C 3 2 C 9 2 0.6267 2.4680 30 0.25 0.8013 Tukey-Kramer 1.0000 0.05 -4.4136 5.6670 -9.3932 10.6466
hospbi*age_gr*sample C 3 2 A 9 3 -0.5471 1.6943 30 -0.32 0.7490 Tukey-Kramer 1.0000 0.05 -4.0074 2.9131 -7.4259 6.3317
hospbi*age_gr*sample C 3 2 B 9 3 -0.3865 1.6815 30 -0.23 0.8198 Tukey-Kramer 1.0000 0.05 -3.8207 3.0476 -7.2135 6.4404
hospbi*age_gr*sample C 3 2 C 9 3 -0.6981 1.5931 30 -0.44 0.6644 Tukey-Kramer 1.0000 0.05 -3.9516 2.5554 -7.1659 5.7697
hospbi*age_gr*sample A 3 3 B 3 3 -0.00453 0.1391 30 -0.03 0.9742 Tukey-Kramer 1.0000 0.05 -0.2886 0.2795 -0.5693 0.5602
hospbi*age_gr*sample A 3 3 C 3 3 -0.06527 0.2698 30 -0.24 0.8105 Tukey-Kramer 1.0000 0.05 -0.6164 0.4858 -1.1608 1.0303
hospbi*age_gr*sample A 3 3 A 6 1 -0.7601 1.5878 30 -0.48 0.6356 Tukey-Kramer 1.0000 0.05 -4.0029 2.4826 -7.2065 5.6863
hospbi*age_gr*sample A 3 3 B 6 1 -1.1233 1.5604 30 -0.72 0.4772 Tukey-Kramer 1.0000 0.05 -4.3100 2.0635 -7.4584 5.2119
hospbi*age_gr*sample A 3 3 C 6 1 -0.7653 1.3622 30 -0.56 0.5784 Tukey-Kramer 1.0000 0.05 -3.5473 2.0166 -6.2957 4.7650
hospbi*age_gr*sample A 3 3 A 6 2 0.05475 2.0498 30 0.03 0.9789 Tukey-Kramer 1.0000 0.05 -4.1316 4.2411 -8.2675 8.3770
hospbi*age_gr*sample A 3 3 B 6 2 0.08140 2.0073 30 0.04 0.9679 Tukey-Kramer 1.0000 0.05 -4.0181 4.1809 -8.0682 8.2310
hospbi*age_gr*sample A 3 3 C 6 2 -0.03941 1.6943 30 -0.02 0.9816 Tukey-Kramer 1.0000 0.05 -3.4997 3.4208 -6.9182 6.8394
hospbi*age_gr*sample A 3 3 A 6 3 -0.04886 1.3419 30 -0.04 0.9712 Tukey-Kramer 1.0000 0.05 -2.7895 2.6917 -5.4971 5.3993
hospbi*age_gr*sample A 3 3 B 6 3 -0.2199 1.3234 30 -0.17 0.8691 Tukey-Kramer 1.0000 0.05 -2.9228 2.4829 -5.5931 5.1532
hospbi*age_gr*sample A 3 3 C 6 3 -0.2014 1.1918 30 -0.17 0.8669 Tukey-Kramer 1.0000 0.05 -2.6355 2.2326 -5.0402 4.6374
hospbi*age_gr*sample A 3 3 A 9 1 -3.8704 1.5878 30 -2.44 0.0209 Tukey-Kramer 0.7526 0.05 -7.1132 -0.6277 -10.3168 2.5760
hospbi*age_gr*sample A 3 3 B 9 1 -3.5253 1.5604 30 -2.26 0.0313 Tukey-Kramer 0.8483 0.05 -6.7121 -0.3385 -9.8604 2.8099
hospbi*age_gr*sample A 3 3 C 9 1 -2.7241 1.3622 30 -2.00 0.0546 Tukey-Kramer 0.9432 0.05 -5.5060 0.05785 -8.2545 2.8063
hospbi*age_gr*sample A 3 3 A 9 2 -0.03773 2.7502 30 -0.01 0.9891 Tukey-Kramer 1.0000 0.05 -5.6543 5.5788 -11.2032 11.1278
hospbi*age_gr*sample A 3 3 B 9 2 0.01600 2.6867 30 0.01 0.9953 Tukey-Kramer 1.0000 0.05 -5.4710 5.5030 -10.8918 10.9238
hospbi*age_gr*sample A 3 3 C 9 2 0.02567 2.2138 30 0.01 0.9908 Tukey-Kramer 1.0000 0.05 -4.4956 4.5469 -8.9624 9.0137
hospbi*age_gr*sample A 3 3 A 9 3 -1.1481 1.2964 30 -0.89 0.3829 Tukey-Kramer 1.0000 0.05 -3.7958 1.4996 -6.4116 4.1153
hospbi*age_gr*sample A 3 3 B 9 3 -0.9875 1.2797 30 -0.77 0.4463 Tukey-Kramer 1.0000 0.05 -3.6010 1.6260 -6.1830 4.2080
hospbi*age_gr*sample A 3 3 C 9 3 -1.2991 1.1610 30 -1.12 0.2720 Tukey-Kramer 1.0000 0.05 -3.6702 1.0720 -6.0128 3.4146
hospbi*age_gr*sample B 3 3 C 3 3 -0.06073 0.2259 30 -0.27 0.7899 Tukey-Kramer 1.0000 0.05 -0.5221 0.4006 -0.9779 0.8565
hospbi*age_gr*sample B 3 3 A 6 1 -0.7556 1.5742 30 -0.48 0.6347 Tukey-Kramer 1.0000 0.05 -3.9705 2.4593 -7.1466 5.6354
hospbi*age_gr*sample B 3 3 B 6 1 -1.1187 1.5465 30 -0.72 0.4750 Tukey-Kramer 1.0000 0.05 -4.2772 2.0397 -7.3975 5.1601
hospbi*age_gr*sample B 3 3 C 6 1 -0.7608 1.3463 30 -0.57 0.5762 Tukey-Kramer 1.0000 0.05 -3.5102 1.9886 -6.2265 4.7049
hospbi*age_gr*sample B 3 3 A 6 2 0.05928 2.0393 30 0.03 0.9770 Tukey-Kramer 1.0000 0.05 -4.1055 4.2241 -8.2202 8.3387
hospbi*age_gr*sample B 3 3 B 6 2 0.08593 1.9966 30 0.04 0.9660 Tukey-Kramer 1.0000 0.05 -3.9916 4.1634 -8.0200 8.1918
hospbi*age_gr*sample B 3 3 C 6 2 -0.03488 1.6815 30 -0.02 0.9836 Tukey-Kramer 1.0000 0.05 -3.4690 3.3993 -6.8618 6.7921
hospbi*age_gr*sample B 3 3 A 6 3 -0.04433 1.3258 30 -0.03 0.9735 Tukey-Kramer 1.0000 0.05 -2.7519 2.6633 -5.4269 5.3382
hospbi*age_gr*sample B 3 3 B 6 3 -0.2154 1.3071 30 -0.16 0.8702 Tukey-Kramer 1.0000 0.05 -2.8848 2.4539 -5.5220 5.0911
hospbi*age_gr*sample B 3 3 C 6 3 -0.1969 1.1736 30 -0.17 0.8679 Tukey-Kramer 1.0000 0.05 -2.5937 2.1999 -4.9616 4.5679
hospbi*age_gr*sample B 3 3 A 9 1 -3.8659 1.5742 30 -2.46 0.0201 Tukey-Kramer 0.7417 0.05 -7.0808 -0.6510 -10.2569 2.5251
hospbi*age_gr*sample B 3 3 B 9 1 -3.5208 1.5465 30 -2.28 0.0301 Tukey-Kramer 0.8400 0.05 -6.6792 -0.3623 -9.7996 2.7580
hospbi*age_gr*sample B 3 3 C 9 1 -2.7196 1.3463 30 -2.02 0.0524 Tukey-Kramer 0.9378 0.05 -5.4690 0.02986 -8.1853 2.7462
hospbi*age_gr*sample B 3 3 A 9 2 -0.03320 2.7423 30 -0.01 0.9904 Tukey-Kramer 1.0000 0.05 -5.6337 5.5673 -11.1668 11.1004
hospbi*age_gr*sample B 3 3 B 9 2 0.02053 2.6787 30 0.01 0.9939 Tukey-Kramer 1.0000 0.05 -5.4500 5.4911 -10.8547 10.8957
hospbi*age_gr*sample B 3 3 C 9 2 0.03020 2.2041 30 0.01 0.9892 Tukey-Kramer 1.0000 0.05 -4.4711 4.5315 -8.9182 8.9786
hospbi*age_gr*sample B 3 3 A 9 3 -1.1436 1.2797 30 -0.89 0.3786 Tukey-Kramer 1.0000 0.05 -3.7571 1.4699 -6.3391 4.0519
hospbi*age_gr*sample B 3 3 B 9 3 -0.9830 1.2627 30 -0.78 0.4424 Tukey-Kramer 1.0000 0.05 -3.5618 1.5959 -6.1096 4.1436
hospbi*age_gr*sample B 3 3 C 9 3 -1.2946 1.1423 30 -1.13 0.2661 Tukey-Kramer 1.0000 0.05 -3.6274 1.0383 -5.9322 3.3431
hospbi*age_gr*sample C 3 3 A 6 1 -0.6949 1.4793 30 -0.47 0.6419 Tukey-Kramer 1.0000 0.05 -3.7160 2.3263 -6.7008 5.3110
hospbi*age_gr*sample C 3 3 B 6 1 -1.0580 1.4499 30 -0.73 0.4712 Tukey-Kramer 1.0000 0.05 -4.0190 1.9030 -6.9443 4.8283
hospbi*age_gr*sample C 3 3 C 6 1 -0.7001 1.2340 30 -0.57 0.5747 Tukey-Kramer 1.0000 0.05 -3.2202 1.8201 -5.7100 4.3099
hospbi*age_gr*sample C 3 3 A 6 2 0.1200 1.9670 30 0.06 0.9518 Tukey-Kramer 1.0000 0.05 -3.8971 4.1372 -7.8659 8.1059
hospbi*age_gr*sample C 3 3 B 6 2 0.1467 1.9226 30 0.08 0.9397 Tukey-Kramer 1.0000 0.05 -3.7799 4.0732 -7.6592 7.9525
hospbi*age_gr*sample C 3 3 C 6 2 0.02586 1.5931 30 0.02 0.9872 Tukey-Kramer 1.0000 0.05 -3.2277 3.2794 -6.4420 6.4937
hospbi*age_gr*sample C 3 3 A 6 3 0.01640 1.2116 30 0.01 0.9893 Tukey-Kramer 1.0000 0.05 -2.4580 2.4908 -4.9027 4.9355
hospbi*age_gr*sample C 3 3 B 6 3 -0.1547 1.1911 30 -0.13 0.8975 Tukey-Kramer 1.0000 0.05 -2.5872 2.2779 -4.9905 4.6811
hospbi*age_gr*sample C 3 3 C 6 3 -0.1362 1.0429 30 -0.13 0.8970 Tukey-Kramer 1.0000 0.05 -2.2661 1.9938 -4.3703 4.0980
hospbi*age_gr*sample C 3 3 A 9 1 -3.8052 1.4793 30 -2.57 0.0153 Tukey-Kramer 0.6690 0.05 -6.8263 -0.7840 -9.8111 2.2007
hospbi*age_gr*sample C 3 3 B 9 1 -3.4600 1.4499 30 -2.39 0.0235 Tukey-Kramer 0.7822 0.05 -6.4210 -0.4990 -9.3463 2.4263
hospbi*age_gr*sample C 3 3 C 9 1 -2.6588 1.2340 30 -2.15 0.0393 Tukey-Kramer 0.8934 0.05 -5.1790 -0.1387 -7.6688 2.3511
hospbi*age_gr*sample C 3 3 A 9 2 0.02754 2.6890 30 0.01 0.9919 Tukey-Kramer 1.0000 0.05 -5.4641 5.5192 -10.8896 10.9446
hospbi*age_gr*sample C 3 3 B 9 2 0.08127 2.6240 30 0.03 0.9755 Tukey-Kramer 1.0000 0.05 -5.2777 5.4403 -10.5722 10.7347
hospbi*age_gr*sample C 3 3 C 9 2 0.09093 2.1373 30 0.04 0.9663 Tukey-Kramer 1.0000 0.05 -4.2741 4.4560 -8.5866 8.7684
hospbi*age_gr*sample C 3 3 A 9 3 -1.0829 1.1610 30 -0.93 0.3584 Tukey-Kramer 1.0000 0.05 -3.4540 1.2883 -5.7965 3.6308
hospbi*age_gr*sample C 3 3 B 9 3 -0.9223 1.1423 30 -0.81 0.4258 Tukey-Kramer 1.0000 0.05 -3.2551 1.4106 -5.5599 3.7154
hospbi*age_gr*sample C 3 3 C 9 3 -1.2338 1.0076 30 -1.22 0.2303 Tukey-Kramer 0.9999 0.05 -3.2915 0.8239 -5.3244 2.8568
hospbi*age_gr*sample A 6 1 B 6 1 -0.3631 0.1967 30 -1.85 0.0748 Tukey-Kramer 0.9740 0.05 -0.7649 0.03862 -1.1618 0.4355
hospbi*age_gr*sample A 6 1 C 6 1 -0.00520 0.3816 30 -0.01 0.9892 Tukey-Kramer 1.0000 0.05 -0.7846 0.7742 -1.5546 1.5441
hospbi*age_gr*sample A 6 1 A 6 2 0.8149 2.2455 30 0.36 0.7192 Tukey-Kramer 1.0000 0.05 -3.7710 5.4008 -8.3017 9.9315
hospbi*age_gr*sample A 6 1 B 6 2 0.8415 2.2067 30 0.38 0.7056 Tukey-Kramer 1.0000 0.05 -3.6652 5.3483 -8.1177 9.8008
hospbi*age_gr*sample A 6 1 C 6 2 0.7207 1.9264 30 0.37 0.7109 Tukey-Kramer 1.0000 0.05 -3.2135 4.6550 -7.1004 8.5419
hospbi*age_gr*sample A 6 1 A 6 3 0.7113 1.6252 30 0.44 0.6648 Tukey-Kramer 1.0000 0.05 -2.6078 4.0303 -5.8868 7.3094
hospbi*age_gr*sample A 6 1 B 6 3 0.5402 1.6099 30 0.34 0.7396 Tukey-Kramer 1.0000 0.05 -2.7477 3.8281 -5.9961 7.0764
hospbi*age_gr*sample A 6 1 C 6 3 0.5587 1.5036 30 0.37 0.7128 Tukey-Kramer 1.0000 0.05 -2.5121 3.6295 -5.5459 6.6633
hospbi*age_gr*sample A 6 1 A 9 1 -3.1103 1.8334 30 -1.70 0.1002 Tukey-Kramer 0.9898 0.05 -6.8547 0.6341 -10.5540 4.3334
hospbi*age_gr*sample A 6 1 B 9 1 -2.7652 1.8098 30 -1.53 0.1370 Tukey-Kramer 0.9973 0.05 -6.4612 0.9309 -10.1127 4.5824
hospbi*age_gr*sample A 6 1 C 9 1 -1.9640 1.6419 30 -1.20 0.2410 Tukey-Kramer 0.9999 0.05 -5.3172 1.3893 -8.6301 4.7022
hospbi*age_gr*sample A 6 1 A 9 2 0.7224 2.8989 30 0.25 0.8049 Tukey-Kramer 1.0000 0.05 -5.1980 6.6428 -11.0471 12.4919
hospbi*age_gr*sample A 6 1 B 9 2 0.7761 2.8388 30 0.27 0.7864 Tukey-Kramer 1.0000 0.05 -5.0214 6.5737 -10.7492 12.3015
hospbi*age_gr*sample A 6 1 C 9 2 0.7858 2.3961 30 0.33 0.7452 Tukey-Kramer 1.0000 0.05 -4.1077 5.6793 -8.9423 10.5139
hospbi*age_gr*sample A 6 1 A 9 3 -0.3880 1.5878 30 -0.24 0.8086 Tukey-Kramer 1.0000 0.05 -3.6307 2.8547 -6.8344 6.0584
hospbi*age_gr*sample A 6 1 B 9 3 -0.2274 1.5742 30 -0.14 0.8861 Tukey-Kramer 1.0000 0.05 -3.4422 2.9875 -6.6184 6.1636
hospbi*age_gr*sample A 6 1 C 9 3 -0.5390 1.4793 30 -0.36 0.7182 Tukey-Kramer 1.0000 0.05 -3.5601 2.4822 -6.5448 5.4669
hospbi*age_gr*sample B 6 1 C 6 1 0.3579 0.3195 30 1.12 0.2715 Tukey-Kramer 1.0000 0.05 -0.2946 1.0104 -0.9392 1.6550
hospbi*age_gr*sample B 6 1 A 6 2 1.1780 2.2262 30 0.53 0.6006 Tukey-Kramer 1.0000 0.05 -3.3685 5.7245 -7.8603 10.2163
hospbi*age_gr*sample B 6 1 B 6 2 1.2047 2.1871 30 0.55 0.5858 Tukey-Kramer 1.0000 0.05 -3.2620 5.6713 -7.6749 10.0842
hospbi*age_gr*sample B 6 1 C 6 2 1.0839 1.9039 30 0.57 0.5734 Tukey-Kramer 1.0000 0.05 -2.8044 4.9721 -6.6459 8.8136
hospbi*age_gr*sample B 6 1 A 6 3 1.0744 1.5984 30 0.67 0.5066 Tukey-Kramer 1.0000 0.05 -2.1900 4.3388 -5.4151 7.5639
hospbi*age_gr*sample B 6 1 B 6 3 0.9033 1.5829 30 0.57 0.5725 Tukey-Kramer 1.0000 0.05 -2.3294 4.1361 -5.5232 7.3299
hospbi*age_gr*sample B 6 1 C 6 3 0.9218 1.4746 30 0.63 0.5366 Tukey-Kramer 1.0000 0.05 -2.0898 3.9335 -5.0652 6.9088
hospbi*age_gr*sample B 6 1 A 9 1 -2.7472 1.8098 30 -1.52 0.1395 Tukey-Kramer 0.9975 0.05 -6.4432 0.9488 -10.0947 4.6004
hospbi*age_gr*sample B 6 1 B 9 1 -2.4020 1.7858 30 -1.35 0.1887 Tukey-Kramer 0.9996 0.05 -6.0491 1.2450 -9.6522 4.8481
hospbi*age_gr*sample B 6 1 C 9 1 -1.6008 1.6154 30 -0.99 0.3296 Tukey-Kramer 1.0000 0.05 -4.9000 1.6983 -8.1594 4.9578
hospbi*age_gr*sample B 6 1 A 9 2 1.0855 2.8840 30 0.38 0.7093 Tukey-Kramer 1.0000 0.05 -4.8044 6.9755 -10.6234 12.7944
hospbi*age_gr*sample B 6 1 B 9 2 1.1393 2.8236 30 0.40 0.6895 Tukey-Kramer 1.0000 0.05 -4.6272 6.9057 -10.3242 12.6027
hospbi*age_gr*sample B 6 1 C 9 2 1.1489 2.3781 30 0.48 0.6325 Tukey-Kramer 1.0000 0.05 -3.7077 6.0056 -8.5058 10.8037
hospbi*age_gr*sample B 6 1 A 9 3 -0.02486 1.5604 30 -0.02 0.9874 Tukey-Kramer 1.0000 0.05 -3.2116 3.1619 -6.3600 6.3103
hospbi*age_gr*sample B 6 1 B 9 3 0.1357 1.5465 30 0.09 0.9306 Tukey-Kramer 1.0000 0.05 -3.0227 3.2942 -6.1431 6.4145
hospbi*age_gr*sample B 6 1 C 9 3 -0.1758 1.4499 30 -0.12 0.9043 Tukey-Kramer 1.0000 0.05 -3.1368 2.7852 -6.0622 5.7105
hospbi*age_gr*sample C 6 1 A 6 2 0.8201 2.0920 30 0.39 0.6978 Tukey-Kramer 1.0000 0.05 -3.4524 5.0926 -7.6735 9.3137
hospbi*age_gr*sample C 6 1 B 6 2 0.8467 2.0504 30 0.41 0.6826 Tukey-Kramer 1.0000 0.05 -3.3407 5.0342 -7.4778 9.1713
hospbi*age_gr*sample C 6 1 C 6 2 0.7259 1.7451 30 0.42 0.6804 Tukey-Kramer 1.0000 0.05 -2.8381 4.2900 -6.3592 7.8111
hospbi*age_gr*sample C 6 1 A 6 3 0.7165 1.4056 30 0.51 0.6140 Tukey-Kramer 1.0000 0.05 -2.1541 3.5870 -4.9900 6.4230
hospbi*age_gr*sample C 6 1 B 6 3 0.5454 1.3879 30 0.39 0.6971 Tukey-Kramer 1.0000 0.05 -2.2891 3.3799 -5.0895 6.1802
hospbi*age_gr*sample C 6 1 C 6 3 0.5639 1.2630 30 0.45 0.6585 Tukey-Kramer 1.0000 0.05 -2.0155 3.1434 -4.5639 5.6918
hospbi*age_gr*sample C 6 1 A 9 1 -3.1051 1.6419 30 -1.89 0.0683 Tukey-Kramer 0.9667 0.05 -6.4584 0.2481 -9.7712 3.5610
hospbi*age_gr*sample C 6 1 B 9 1 -2.7599 1.6154 30 -1.71 0.0979 Tukey-Kramer 0.9889 0.05 -6.0591 0.5392 -9.3186 3.7987
hospbi*age_gr*sample C 6 1 C 9 1 -1.9588 1.4249 30 -1.37 0.1794 Tukey-Kramer 0.9994 0.05 -4.8688 0.9513 -7.7438 3.8262
hospbi*age_gr*sample C 6 1 A 9 2 0.7276 2.7818 30 0.26 0.7954 Tukey-Kramer 1.0000 0.05 -4.9535 6.4087 -10.5662 12.0214
hospbi*age_gr*sample C 6 1 B 9 2 0.7813 2.7190 30 0.29 0.7758 Tukey-Kramer 1.0000 0.05 -4.7717 6.3343 -10.2578 11.8205
hospbi*age_gr*sample C 6 1 C 9 2 0.7910 2.2530 30 0.35 0.7280 Tukey-Kramer 1.0000 0.05 -3.8101 5.3922 -8.3559 9.9379
hospbi*age_gr*sample C 6 1 A 9 3 -0.3828 1.3622 30 -0.28 0.7806 Tukey-Kramer 1.0000 0.05 -3.1647 2.3992 -5.9132 5.1476
hospbi*age_gr*sample C 6 1 B 9 3 -0.2222 1.3463 30 -0.17 0.8700 Tukey-Kramer 1.0000 0.05 -2.9716 2.5272 -5.6879 5.2436
hospbi*age_gr*sample C 6 1 C 9 3 -0.5338 1.2340 30 -0.43 0.6684 Tukey-Kramer 1.0000 0.05 -3.0539 1.9864 -5.5437 4.4762
hospbi*age_gr*sample A 6 2 B 6 2 0.02665 0.2782 30 0.10 0.9243 Tukey-Kramer 1.0000 0.05 -0.5415 0.5948 -1.1028 1.1561
hospbi*age_gr*sample A 6 2 C 6 2 -0.09415 0.5397 30 -0.17 0.8627 Tukey-Kramer 1.0000 0.05 -1.1963 1.0080 -2.2853 2.0970
hospbi*age_gr*sample A 6 2 A 6 3 -0.1036 2.0789 30 -0.05 0.9606 Tukey-Kramer 1.0000 0.05 -4.3493 4.1421 -8.5439 8.3367
hospbi*age_gr*sample A 6 2 B 6 3 -0.2747 2.0670 30 -0.13 0.8952 Tukey-Kramer 1.0000 0.05 -4.4961 3.9468 -8.6667 8.1174
hospbi*age_gr*sample A 6 2 C 6 3 -0.2562 1.9853 30 -0.13 0.8982 Tukey-Kramer 1.0000 0.05 -4.3108 3.7984 -8.3166 7.8042
hospbi*age_gr*sample A 6 2 A 9 1 -3.9252 2.2455 30 -1.75 0.0907 Tukey-Kramer 0.9856 0.05 -8.5111 0.6607 -13.0418 5.1914
hospbi*age_gr*sample A 6 2 B 9 1 -3.5800 2.2262 30 -1.61 0.1183 Tukey-Kramer 0.9947 0.05 -8.1265 0.9665 -12.6183 5.4582
hospbi*age_gr*sample A 6 2 C 9 1 -2.7788 2.0920 30 -1.33 0.1941 Tukey-Kramer 0.9996 0.05 -7.0514 1.4937 -11.2724 5.7148
hospbi*age_gr*sample A 6 2 A 9 2 -0.09247 3.1756 30 -0.03 0.9770 Tukey-Kramer 1.0000 0.05 -6.5779 6.3930 -12.9853 12.8003
hospbi*age_gr*sample A 6 2 B 9 2 -0.03874 3.1208 30 -0.01 0.9902 Tukey-Kramer 1.0000 0.05 -6.4123 6.3348 -12.7091 12.6316
hospbi*age_gr*sample A 6 2 C 9 2 -0.02908 2.7244 30 -0.01 0.9916 Tukey-Kramer 1.0000 0.05 -5.5930 5.5348 -11.0898 11.0317
hospbi*age_gr*sample A 6 2 A 9 3 -1.2029 2.0498 30 -0.59 0.5617 Tukey-Kramer 1.0000 0.05 -5.3892 2.9835 -9.5251 7.1194
hospbi*age_gr*sample A 6 2 B 9 3 -1.0423 2.0393 30 -0.51 0.6130 Tukey-Kramer 1.0000 0.05 -5.2071 3.1225 -9.3217 7.2372
hospbi*age_gr*sample A 6 2 C 9 3 -1.3538 1.9670 30 -0.69 0.4966 Tukey-Kramer 1.0000 0.05 -5.3710 2.6633 -9.3397 6.6321
hospbi*age_gr*sample B 6 2 C 6 2 -0.1208 0.4518 30 -0.27 0.7910 Tukey-Kramer 1.0000 0.05 -1.0436 0.8019 -1.9552 1.7136
hospbi*age_gr*sample B 6 2 A 6 3 -0.1303 2.0370 30 -0.06 0.9494 Tukey-Kramer 1.0000 0.05 -4.2904 4.0299 -8.4004 8.1399
hospbi*age_gr*sample B 6 2 B 6 3 -0.3013 2.0249 30 -0.15 0.8827 Tukey-Kramer 1.0000 0.05 -4.4367 3.8340 -8.5222 7.9195
hospbi*age_gr*sample B 6 2 C 6 3 -0.2828 1.9414 30 -0.15 0.8851 Tukey-Kramer 1.0000 0.05 -4.2477 3.6821 -8.1648 7.5992
hospbi*age_gr*sample B 6 2 A 9 1 -3.9518 2.2067 30 -1.79 0.0834 Tukey-Kramer 0.9812 0.05 -8.4586 0.5549 -12.9111 5.0074
hospbi*age_gr*sample B 6 2 B 9 1 -3.6067 2.1871 30 -1.65 0.1096 Tukey-Kramer 0.9928 0.05 -8.0734 0.8600 -12.4863 5.2729
hospbi*age_gr*sample B 6 2 C 9 1 -2.8055 2.0504 30 -1.37 0.1814 Tukey-Kramer 0.9994 0.05 -6.9930 1.3820 -11.1300 5.5190
hospbi*age_gr*sample B 6 2 A 9 2 -0.1191 3.1483 30 -0.04 0.9701 Tukey-Kramer 1.0000 0.05 -6.5489 6.3106 -12.9012 12.6629
hospbi*age_gr*sample B 6 2 B 9 2 -0.06540 3.0930 30 -0.02 0.9833 Tukey-Kramer 1.0000 0.05 -6.3822 6.2514 -12.6230 12.4922
hospbi*age_gr*sample B 6 2 C 9 2 -0.05573 2.6925 30 -0.02 0.9836 Tukey-Kramer 1.0000 0.05 -5.5546 5.4431 -10.9872 10.8757
hospbi*age_gr*sample B 6 2 A 9 3 -1.2295 2.0073 30 -0.61 0.5448 Tukey-Kramer 1.0000 0.05 -5.3290 2.8700 -9.3791 6.9201
hospbi*age_gr*sample B 6 2 B 9 3 -1.0689 1.9966 30 -0.54 0.5963 Tukey-Kramer 1.0000 0.05 -5.1464 3.0086 -9.1748 7.0370
hospbi*age_gr*sample B 6 2 C 9 3 -1.3805 1.9226 30 -0.72 0.4783 Tukey-Kramer 1.0000 0.05 -5.3071 2.5461 -9.1863 6.4253
hospbi*age_gr*sample C 6 2 A 6 3 -0.00946 1.7294 30 -0.01 0.9957 Tukey-Kramer 1.0000 0.05 -3.5413 3.5224 -7.0306 7.0117
hospbi*age_gr*sample C 6 2 B 6 3 -0.1805 1.7151 30 -0.11 0.9169 Tukey-Kramer 1.0000 0.05 -3.6832 3.3221 -7.1436 6.7826
hospbi*age_gr*sample C 6 2 C 6 3 -0.1620 1.6157 30 -0.10 0.9208 Tukey-Kramer 1.0000 0.05 -3.4617 3.1376 -6.7216 6.3976
hospbi*age_gr*sample C 6 2 A 9 1 -3.8310 1.9264 30 -1.99 0.0559 Tukey-Kramer 0.9460 0.05 -7.7653 0.1032 -11.6522 3.9901
hospbi*age_gr*sample C 6 2 B 9 1 -3.4859 1.9039 30 -1.83 0.0771 Tukey-Kramer 0.9761 0.05 -7.3742 0.4024 -11.2156 4.2438
hospbi*age_gr*sample C 6 2 C 9 1 -2.6847 1.7451 30 -1.54 0.1344 Tukey-Kramer 0.9970 0.05 -6.2487 0.8794 -9.7698 4.4005
hospbi*age_gr*sample C 6 2 A 9 2 0.001681 2.9586 30 0.00 0.9996 Tukey-Kramer 1.0000 0.05 -6.0406 6.0439 -12.0101 12.0134
hospbi*age_gr*sample C 6 2 B 9 2 0.05541 2.8997 30 0.02 0.9849 Tukey-Kramer 1.0000 0.05 -5.8666 5.9774 -11.7172 11.8281
hospbi*age_gr*sample C 6 2 C 9 2 0.06508 2.4680 30 0.03 0.9791 Tukey-Kramer 1.0000 0.05 -4.9752 5.1054 -9.9548 10.0850
hospbi*age_gr*sample C 6 2 A 9 3 -1.1087 1.6943 30 -0.65 0.5179 Tukey-Kramer 1.0000 0.05 -4.5690 2.3515 -7.9875 5.7701
hospbi*age_gr*sample C 6 2 B 9 3 -0.9481 1.6815 30 -0.56 0.5771 Tukey-Kramer 1.0000 0.05 -4.3823 2.4861 -7.7751 5.8789
hospbi*age_gr*sample C 6 2 C 9 3 -1.2597 1.5931 30 -0.79 0.4353 Tukey-Kramer 1.0000 0.05 -4.5132 1.9938 -7.7275 5.2081
hospbi*age_gr*sample A 6 3 B 6 3 -0.1711 0.1487 30 -1.15 0.2590 Tukey-Kramer 1.0000 0.05 -0.4748 0.1326 -0.7748 0.4326
hospbi*age_gr*sample A 6 3 C 6 3 -0.1526 0.2885 30 -0.53 0.6008 Tukey-Kramer 1.0000 0.05 -0.7417 0.4366 -1.3238 1.0186
hospbi*age_gr*sample A 6 3 A 9 1 -3.8216 1.6252 30 -2.35 0.0255 Tukey-Kramer 0.8015 0.05 -7.1406 -0.5025 -10.4197 2.7765
hospbi*age_gr*sample A 6 3 B 9 1 -3.4764 1.5984 30 -2.17 0.0377 Tukey-Kramer 0.8853 0.05 -6.7408 -0.2120 -9.9659 3.0130
hospbi*age_gr*sample A 6 3 C 9 1 -2.6752 1.4056 30 -1.90 0.0666 Tukey-Kramer 0.9645 0.05 -5.5458 0.1953 -8.3817 3.0313
hospbi*age_gr*sample A 6 3 A 9 2 0.01114 2.7719 30 0.00 0.9968 Tukey-Kramer 1.0000 0.05 -5.6498 5.6721 -11.2426 11.2649
hospbi*age_gr*sample A 6 3 B 9 2 0.06487 2.7089 30 0.02 0.9811 Tukey-Kramer 1.0000 0.05 -5.4675 5.5973 -10.9333 11.0630
hospbi*age_gr*sample A 6 3 C 9 2 0.07453 2.2408 30 0.03 0.9737 Tukey-Kramer 1.0000 0.05 -4.5017 4.6508 -9.0229 9.1720
hospbi*age_gr*sample A 6 3 A 9 3 -1.0993 1.3419 30 -0.82 0.4192 Tukey-Kramer 1.0000 0.05 -3.8399 1.6414 -6.5475 4.3490
hospbi*age_gr*sample A 6 3 B 9 3 -0.9387 1.3258 30 -0.71 0.4844 Tukey-Kramer 1.0000 0.05 -3.6462 1.7689 -6.3212 4.4439
hospbi*age_gr*sample A 6 3 C 9 3 -1.2502 1.2116 30 -1.03 0.3104 Tukey-Kramer 1.0000 0.05 -3.7247 1.2242 -6.1693 3.6689
hospbi*age_gr*sample B 6 3 C 6 3 0.01852 0.2415 30 0.08 0.9394 Tukey-Kramer 1.0000 0.05 -0.4747 0.5118 -0.9620 0.9990
hospbi*age_gr*sample B 6 3 A 9 1 -3.6505 1.6099 30 -2.27 0.0307 Tukey-Kramer 0.8444 0.05 -6.9384 -0.3626 -10.1867 2.8857
hospbi*age_gr*sample B 6 3 B 9 1 -3.3053 1.5829 30 -2.09 0.0454 Tukey-Kramer 0.9172 0.05 -6.5381 -0.07260 -9.7319 3.1212
hospbi*age_gr*sample B 6 3 C 9 1 -2.5042 1.3879 30 -1.80 0.0812 Tukey-Kramer 0.9796 0.05 -5.3386 0.3303 -8.1390 3.1307
hospbi*age_gr*sample B 6 3 A 9 2 0.1822 2.7630 30 0.07 0.9479 Tukey-Kramer 1.0000 0.05 -5.4606 5.8250 -11.0354 11.3998
hospbi*age_gr*sample B 6 3 B 9 2 0.2359 2.6998 30 0.09 0.9309 Tukey-Kramer 1.0000 0.05 -5.2778 5.7497 -10.7252 11.1971
hospbi*age_gr*sample B 6 3 C 9 2 0.2456 2.2298 30 0.11 0.9130 Tukey-Kramer 1.0000 0.05 -4.3081 4.7994 -8.8071 9.2983
hospbi*age_gr*sample B 6 3 A 9 3 -0.9282 1.3234 30 -0.70 0.4885 Tukey-Kramer 1.0000 0.05 -3.6310 1.7747 -6.3013 4.4450
hospbi*age_gr*sample B 6 3 B 9 3 -0.7676 1.3071 30 -0.59 0.5614 Tukey-Kramer 1.0000 0.05 -3.4369 1.9018 -6.0741 4.5390
hospbi*age_gr*sample B 6 3 C 9 3 -1.0792 1.1911 30 -0.91 0.3721 Tukey-Kramer 1.0000 0.05 -3.5117 1.3534 -5.9150 3.7566
hospbi*age_gr*sample C 6 3 A 9 1 -3.6690 1.5036 30 -2.44 0.0208 Tukey-Kramer 0.7511 0.05 -6.7398 -0.5982 -9.7736 2.4356
hospbi*age_gr*sample C 6 3 B 9 1 -3.3239 1.4746 30 -2.25 0.0317 Tukey-Kramer 0.8508 0.05 -6.3355 -0.3122 -9.3109 2.6631
hospbi*age_gr*sample C 6 3 C 9 1 -2.5227 1.2630 30 -2.00 0.0549 Tukey-Kramer 0.9439 0.05 -5.1021 0.05679 -7.6505 2.6052
hospbi*age_gr*sample C 6 3 A 9 2 0.1637 2.7024 30 0.06 0.9521 Tukey-Kramer 1.0000 0.05 -5.3554 5.6828 -10.8080 11.1354
hospbi*age_gr*sample C 6 3 B 9 2 0.2174 2.6378 30 0.08 0.9349 Tukey-Kramer 1.0000 0.05 -5.1697 5.6046 -10.4919 10.9268
hospbi*age_gr*sample C 6 3 C 9 2 0.2271 2.1542 30 0.11 0.9167 Tukey-Kramer 1.0000 0.05 -4.1725 4.6266 -8.5190 8.9732
hospbi*age_gr*sample C 6 3 A 9 3 -0.9467 1.1918 30 -0.79 0.4333 Tukey-Kramer 1.0000 0.05 -3.3807 1.4874 -5.7855 3.8921
hospbi*age_gr*sample C 6 3 B 9 3 -0.7861 1.1736 30 -0.67 0.5081 Tukey-Kramer 1.0000 0.05 -3.1829 1.6107 -5.5508 3.9787
hospbi*age_gr*sample C 6 3 C 9 3 -1.0977 1.0429 30 -1.05 0.3010 Tukey-Kramer 1.0000 0.05 -3.2276 1.0322 -5.3319 3.1365
hospbi*age_gr*sample A 9 1 B 9 1 0.3452 0.1967 30 1.75 0.0895 Tukey-Kramer 0.9850 0.05 -0.05658 0.7469 -0.4535 1.1438
hospbi*age_gr*sample A 9 1 C 9 1 1.1464 0.3816 30 3.00 0.0053 Tukey-Kramer 0.3928 0.05 0.3670 1.9257 -0.4030 2.6957
hospbi*age_gr*sample A 9 1 A 9 2 3.8327 2.8989 30 1.32 0.1961 Tukey-Kramer 0.9997 0.05 -2.0877 9.7531 -7.9367 15.6022
hospbi*age_gr*sample A 9 1 B 9 2 3.8864 2.8388 30 1.37 0.1811 Tukey-Kramer 0.9994 0.05 -1.9111 9.6840 -7.6389 15.4118
hospbi*age_gr*sample A 9 1 C 9 2 3.8961 2.3961 30 1.63 0.1144 Tukey-Kramer 0.9939 0.05 -0.9974 8.7897 -5.8320 13.6243
hospbi*age_gr*sample A 9 1 A 9 3 2.7223 1.5878 30 1.71 0.0967 Tukey-Kramer 0.9885 0.05 -0.5204 5.9651 -3.7241 9.1687
hospbi*age_gr*sample A 9 1 B 9 3 2.8829 1.5742 30 1.83 0.0770 Tukey-Kramer 0.9760 0.05 -0.3319 6.0978 -3.5081 9.2740
hospbi*age_gr*sample A 9 1 C 9 3 2.5714 1.4793 30 1.74 0.0924 Tukey-Kramer 0.9865 0.05 -0.4498 5.5925 -3.4345 8.5772
hospbi*age_gr*sample B 9 1 C 9 1 0.8012 0.3195 30 2.51 0.0178 Tukey-Kramer 0.7100 0.05 0.1487 1.4537 -0.4959 2.0983
hospbi*age_gr*sample B 9 1 A 9 2 3.4876 2.8840 30 1.21 0.2360 Tukey-Kramer 0.9999 0.05 -2.4024 9.3775 -8.2213 15.1965
hospbi*age_gr*sample B 9 1 B 9 2 3.5413 2.8236 30 1.25 0.2195 Tukey-Kramer 0.9999 0.05 -2.2252 9.3078 -7.9222 15.0048
hospbi*age_gr*sample B 9 1 C 9 2 3.5510 2.3781 30 1.49 0.1458 Tukey-Kramer 0.9980 0.05 -1.3057 8.4076 -6.1038 13.2057
hospbi*age_gr*sample B 9 1 A 9 3 2.3772 1.5604 30 1.52 0.1381 Tukey-Kramer 0.9974 0.05 -0.8096 5.5639 -3.9580 8.7123
hospbi*age_gr*sample B 9 1 B 9 3 2.5378 1.5465 30 1.64 0.1113 Tukey-Kramer 0.9932 0.05 -0.6206 5.6962 -3.7410 8.8166
hospbi*age_gr*sample B 9 1 C 9 3 2.2262 1.4499 30 1.54 0.1352 Tukey-Kramer 0.9971 0.05 -0.7348 5.1872 -3.6601 8.1125
hospbi*age_gr*sample C 9 1 A 9 2 2.6864 2.7818 30 0.97 0.3419 Tukey-Kramer 1.0000 0.05 -2.9947 8.3675 -8.6074 13.9801
hospbi*age_gr*sample C 9 1 B 9 2 2.7401 2.7190 30 1.01 0.3216 Tukey-Kramer 1.0000 0.05 -2.8129 8.2931 -8.2990 13.7792
hospbi*age_gr*sample C 9 1 C 9 2 2.7498 2.2530 30 1.22 0.2318 Tukey-Kramer 0.9999 0.05 -1.8514 7.3509 -6.3971 11.8967
hospbi*age_gr*sample C 9 1 A 9 3 1.5760 1.3622 30 1.16 0.2564 Tukey-Kramer 1.0000 0.05 -1.2060 4.3579 -3.9544 7.1064
hospbi*age_gr*sample C 9 1 B 9 3 1.7366 1.3463 30 1.29 0.2069 Tukey-Kramer 0.9998 0.05 -1.0128 4.4860 -3.7292 7.2023
hospbi*age_gr*sample C 9 1 C 9 3 1.4250 1.2340 30 1.15 0.2573 Tukey-Kramer 1.0000 0.05 -1.0952 3.9452 -3.5850 6.4350
hospbi*age_gr*sample A 9 2 B 9 2 0.05373 0.3934 30 0.14 0.8923 Tukey-Kramer 1.0000 0.05 -0.7498 0.8572 -1.5436 1.6510
hospbi*age_gr*sample A 9 2 C 9 2 0.06340 0.7632 30 0.08 0.9344 Tukey-Kramer 1.0000 0.05 -1.4953 1.6221 -3.0353 3.1621
hospbi*age_gr*sample A 9 2 A 9 3 -1.1104 2.7502 30 -0.40 0.6893 Tukey-Kramer 1.0000 0.05 -6.7270 4.5062 -12.2759 10.0551
hospbi*age_gr*sample A 9 2 B 9 3 -0.9498 2.7423 30 -0.35 0.7315 Tukey-Kramer 1.0000 0.05 -6.5503 4.6507 -12.0834 10.1838
hospbi*age_gr*sample A 9 2 C 9 3 -1.2614 2.6890 30 -0.47 0.6424 Tukey-Kramer 1.0000 0.05 -6.7530 4.2302 -12.1785 9.6557
hospbi*age_gr*sample B 9 2 C 9 2 0.009668 0.6390 30 0.02 0.9880 Tukey-Kramer 1.0000 0.05 -1.2953 1.3146 -2.5845 2.6039
hospbi*age_gr*sample B 9 2 A 9 3 -1.1641 2.6867 30 -0.43 0.6679 Tukey-Kramer 1.0000 0.05 -6.6511 4.3228 -12.0720 9.7437
hospbi*age_gr*sample B 9 2 B 9 3 -1.0035 2.6787 30 -0.37 0.7106 Tukey-Kramer 1.0000 0.05 -6.4741 4.4670 -11.8787 9.8717
hospbi*age_gr*sample B 9 2 C 9 3 -1.3151 2.6240 30 -0.50 0.6199 Tukey-Kramer 1.0000 0.05 -6.6741 4.0439 -11.9685 9.3383
hospbi*age_gr*sample C 9 2 A 9 3 -1.1738 2.2138 30 -0.53 0.5999 Tukey-Kramer 1.0000 0.05 -5.6950 3.3475 -10.1618 7.8142
hospbi*age_gr*sample C 9 2 B 9 3 -1.0132 2.2041 30 -0.46 0.6491 Tukey-Kramer 1.0000 0.05 -5.5145 3.4881 -9.9616 7.9352
hospbi*age_gr*sample C 9 2 C 9 3 -1.3248 2.1373 30 -0.62 0.5401 Tukey-Kramer 1.0000 0.05 -5.6898 3.0403 -10.0023 7.3527
hospbi*age_gr*sample A 9 3 B 9 3 0.1606 0.1391 30 1.15 0.2574 Tukey-Kramer 1.0000 0.05 -0.1235 0.4447 -0.4041 0.7253
hospbi*age_gr*sample A 9 3 C 9 3 -0.1510 0.2698 30 -0.56 0.5800 Tukey-Kramer 1.0000 0.05 -0.7021 0.4001 -1.2465 0.9446
hospbi*age_gr*sample B 9 3 C 9 3 -0.3116 0.2259 30 -1.38 0.1780 Tukey-Kramer 0.9994 0.05 -0.7730 0.1498 -1.2288 0.6056

Data for supplemental table 2 and Figure 1

In [21]:
/*ls means values by head body and tail*/

DATA ki67_lsmeans1 (drop=age_group);
     set ki67_lsmeans;
     if age_group^="" then delete;
     stain="Ki67          ";
     rename _NAME_=pancreas_region;
run;

PROC print data=ki67_lsmeans1;
run;

/*grand mean values*/

PROC means data=ki67_lsmeans1 mean;
     var lsmean;
     class hospbin;
     output out=ki67_grandmean;
run;

DATA ki67_grandmean (drop=_type_ _freq_ _stat_);
     set ki67_grandmean;
     if _stat_^="MEAN" then delete;
     if hospbin="" then delete;
     pancreas_region="Overall";
     stain="Ki67           ";
run;

/*combine files into 1*/

DATA ki67_fig1;
     set ki67_lsmeans1 ki67_grandmean;
run;

PROC print data=ki67_fig1;
run;
Out[21]:
SAS Output
Obs pancreas_region hospbin LSMEAN stain
1 Head 3 1.48995 Ki67
2 Head 6 0.50260 Ki67
3 Head 9 1.93662 Ki67
4 Body 3 1.70602 Ki67
5 Body 6 0.67179 Ki67
6 Body 9 1.75012 Ki67
7 Tail 3 1.41474 Ki67
8 Tail 6 0.58658 Ki67
9 Tail 9 1.58369 Ki67

The MEANS Procedure

Analysis Variable : LSMEAN
hospbin N Obs Mean
3 3 1.5369035
6 3 0.5869893
9 3 1.7568097

Obs pancreas_region hospbin LSMEAN stain
1 Head 3 1.48995 Ki67
2 Head 6 0.50260 Ki67
3 Head 9 1.93662 Ki67
4 Body 3 1.70602 Ki67
5 Body 6 0.67179 Ki67
6 Body 9 1.75012 Ki67
7 Tail 3 1.41474 Ki67
8 Tail 6 0.58658 Ki67
9 Tail 9 1.58369 Ki67
10 Overall 3 1.53690 Ki67
11 Overall 6 0.58699 Ki67
12 Overall 9 1.75681 Ki67

Ki67/Insulin (dual) dataset

statistical analysis model

In [24]:
PROC glm data=ki67_dual;
     class hospbin age_group;
     model Head Body Tail= hospbin|age_group/nouni; 
     repeated sample_type2 / short printe; 
     lsmeans hospbin|age_group / out=dual_lsmeans(drop=stderr);
run;
quit;

PROC mixed data=ki67;
     class case hospbin age_group sample_type2;
     model percent_dual=hospbin|age_group|sample_type2;
     repeated sample_type2/ subject=case(hospbin) type=un;
     lsmeans hospbin|age_group|sample_type2 /adjust=tukey cl pdiff alpha=0.05;
run;
Out[24]:
SAS Output

The GLM Procedure

Class Level Information
Class Levels Values
hospbin 3 3 6 9
age_group 3 1 2 3
Number of Observations Read 39
Number of Observations Used 39

The GLM Procedure

Repeated Measures Analysis of Variance

Repeated Measures Level Information
Dependent Variable Head Body Tail
Level of sample_type2 1 2 3
Partial Correlation Coefficients from the Error SSCP Matrix / Prob > |r|
DF = 30 Head Body Tail
Head
1.000000
 
0.982131
<.0001
0.991505
<.0001
Body
0.982131
<.0001
1.000000
 
0.996586
<.0001
Tail
0.991505
<.0001
0.996586
<.0001
1.000000
 
E = Error SSCP Matrix

sample_type2_N represents the contrast between the nth level of sample_type2 and the last
  sample_type2_1 sample_type2_2
sample_type2_1 0.957802 -0.175799
sample_type2_2 -0.175799 0.033895
Partial Correlation Coefficients from the Error SSCP Matrix of the Variables Defined by the Specified Transformation / Prob > |r|
DF = 30 sample_type2_1 sample_type2_2
sample_type2_1
1.000000
 
-0.975681
<.0001
sample_type2_2
-0.975681
<.0001
1.000000
 
Sphericity Tests
Variables DF Mauchly's Criterion Chi-Square Pr > ChiSq
Transformed Variates 2 0.0063442 146.74644 <.0001
Orthogonal Components 2 0.0034331 164.55475 <.0001
MANOVA Test Criteria and Exact F Statistics for the Hypothesis of no sample_type2 Effect
H = Type III SSCP Matrix for sample_type2
E = Error SSCP Matrix

S=1 M=0 N=13.5
Statistic Value F Value Num DF Den DF Pr > F
Wilks' Lambda 0.65028907 7.80 2 29 0.0020
Pillai's Trace 0.34971093 7.80 2 29 0.0020
Hotelling-Lawley Trace 0.53777765 7.80 2 29 0.0020
Roy's Greatest Root 0.53777765 7.80 2 29 0.0020
MANOVA Test Criteria and F Approximations for the Hypothesis of no sample_type2*hospbin Effect
H = Type III SSCP Matrix for sample_type2*hospbin
E = Error SSCP Matrix

S=2 M=-0.5 N=13.5
Statistic Value F Value Num DF Den DF Pr > F
NOTE: F Statistic for Roy's Greatest Root is an upper bound.
NOTE: F Statistic for Wilks' Lambda is exact.
Wilks' Lambda 0.61233168 4.03 4 58 0.0060
Pillai's Trace 0.40895024 3.86 4 60 0.0075
Hotelling-Lawley Trace 0.59834631 4.29 4 33.787 0.0065
Roy's Greatest Root 0.53315827 8.00 2 30 0.0016
MANOVA Test Criteria and F Approximations for the Hypothesis of no sample_type2*age_group Effect
H = Type III SSCP Matrix for sample_type2*age_group
E = Error SSCP Matrix

S=2 M=-0.5 N=13.5
Statistic Value F Value Num DF Den DF Pr > F
NOTE: F Statistic for Roy's Greatest Root is an upper bound.
NOTE: F Statistic for Wilks' Lambda is exact.
Wilks' Lambda 0.67224552 3.18 4 58 0.0196
Pillai's Trace 0.34572466 3.13 4 60 0.0208
Hotelling-Lawley Trace 0.46082019 3.31 4 33.787 0.0217
Roy's Greatest Root 0.39275924 5.89 2 30 0.0069
MANOVA Test Criteria and F Approximations for the Hypothesis of no sample_type2*hospbin*age_group Effect
H = Type III SSCP Matrix for sample_type2*hospbin*age_group
E = Error SSCP Matrix

S=2 M=0.5 N=13.5
Statistic Value F Value Num DF Den DF Pr > F
NOTE: F Statistic for Roy's Greatest Root is an upper bound.
NOTE: F Statistic for Wilks' Lambda is exact.
Wilks' Lambda 0.42132407 3.92 8 58 0.0009
Pillai's Trace 0.65936618 3.69 8 60 0.0015
Hotelling-Lawley Trace 1.18195398 4.20 8 39.176 0.0010
Roy's Greatest Root 0.98813931 7.41 4 30 0.0003

The GLM Procedure

Repeated Measures Analysis of Variance

Tests of Hypotheses for Between Subjects Effects

Source DF Type III SS Mean Square F Value Pr > F
hospbin 2 0.23699376 0.11849688 1.23 0.3054
age_group 2 0.56197886 0.28098943 2.93 0.0690
hospbin*age_group 4 0.64108151 0.16027038 1.67 0.1831
Error 30 2.88047805 0.09601594    

The GLM Procedure

Repeated Measures Analysis of Variance

Univariate Tests of Hypotheses for Within Subject Effects

Source DF Type III SS Mean Square F Value Pr > F Adj Pr > F
G - G H-F-L
sample_type2 2 0.04137510 0.02068755 1.59 0.2114 0.2164 0.2164
sample_type2*hospbin 4 0.08368087 0.02092022 1.61 0.1828 0.2161 0.2161
sample_type2*age_group 4 0.12276701 0.03069175 2.37 0.0628 0.1110 0.1110
sample_type2*hospbin*age_group 8 0.20008323 0.02501040 1.93 0.0721 0.1314 0.1314
Error(sample_type2) 60 0.77833063 0.01297218        
Greenhouse-Geisser Epsilon 0.5009
Huynh-Feldt-Lecoutre Epsilon 0.5009

The GLM Procedure

Least Squares Means

hospbin Head LSMEAN
3 0.23147194
6 0.01599092
9 0.02947989
Plot of Head least-squares means for hospbin.
hospbin Body LSMEAN
3 0.07504355
6 0.01401566
9 0.02283059
Plot of Body least-squares means for hospbin.
hospbin Tail LSMEAN
3 0.10131284
6 0.02550048
9 0.02499461
Plot of Tail least-squares means for hospbin.
age_group Head LSMEAN
1 0.26283413
2 0.00957183
3 0.00453678
Plot of Head least-squares means for age_group.
age_group Body LSMEAN
1 0.09955879
2 0.00699655
3 0.00533446
Plot of Body least-squares means for age_group.
age_group Tail LSMEAN
1 0.12511947
2 0.01804942
3 0.00863904
Plot of Tail least-squares means for age_group.
hospbin age_group Head LSMEAN
3 1 0.68773446
3 2 0.00266997
3 3 0.00401140
6 1 0.02151718
6 2 0.02289088
6 3 0.00356470
9 1 0.07925076
9 2 0.00315465
9 3 0.00603425
Plot of Head least-squares means for hospbin*age_group.
hospbin age_group Body LSMEAN
3 1 0.21621333
3 2 0.00368489
3 3 0.00523243
6 1 0.02264907
6 2 0.01579612
6 3 0.00360181
9 1 0.05981397
9 2 0.00150866
9 3 0.00716912
Plot of Body least-squares means for hospbin*age_group.
hospbin age_group Tail LSMEAN
3 1 0.29366926
3 2 0.00319925
3 3 0.00707002
6 1 0.02248340
6 2 0.04729120
6 3 0.00672685
9 1 0.05920576
9 2 0.00365781
9 3 0.01212026
Plot of Tail least-squares means for hospbin*age_group.

The Mixed Procedure

Model Information
Data Set WORK.KI67
Dependent Variable percent_dual
Covariance Structure Unstructured
Subject Effect Case(hospbin)
Estimation Method REML
Residual Variance Method None
Fixed Effects SE Method Model-Based
Degrees of Freedom Method Between-Within
Class Level Information
Class Levels Values
Case 39 6003 6005 6007 6008 6011 6019 6047 6048 6057 6060 6073 6099 6104 6106 6115 6117 6126 6129 6131 6134 6140 6144 6162 6165 6172 6174 6178 6179 6187 6200 6219 6229 6230 6235 6250 6251 6254 6278 6279
hospbin 3 3 6 9
age_group 3 1 2 3
sample_type2 3 A B C
Dimensions
Covariance Parameters 6
Columns in X 64
Columns in Z 0
Subjects 39
Max Obs per Subject 3
Number of Observations
Number of Observations Read 117
Number of Observations Used 117
Number of Observations Not Used 0
Iteration History
Iteration Evaluations -2 Res Log Like Criterion
0 1 1.25531523  
1 1 -324.90184044 0.00000000
Convergence criteria met.
Covariance Parameter Estimates
Cov Parm Subject Estimate
UN(1,1) Case(hospbin) 0.09490
UN(2,1) Case(hospbin) 0.02997
UN(2,2) Case(hospbin) 0.009812
UN(3,1) Case(hospbin) 0.04011
UN(3,2) Case(hospbin) 0.01296
UN(3,3) Case(hospbin) 0.01724
Fit Statistics
-2 Res Log Likelihood -324.9
AIC (Smaller is Better) -312.9
AICC (Smaller is Better) -311.9
BIC (Smaller is Better) -302.9
Null Model Likelihood Ratio Test
DF Chi-Square Pr > ChiSq
5 326.16 <.0001
Type 3 Tests of Fixed Effects
Effect Num DF Den DF F Value Pr > F
hospbin 2 30 1.23 0.3054
age_group 2 30 2.93 0.0690
hospbin*age_group 4 30 1.67 0.1831
sample_type2 2 30 8.07 0.0016
hospbin*sample_type2 4 30 4.49 0.0058
age_group*sample_typ 4 30 3.46 0.0195
hospbi*age_gr*sample 8 30 4.43 0.0013
Least Squares Means
Effect sample_type2 hospbin age_group Estimate Standard
Error
DF t Value Pr > |t| Alpha Lower Upper
hospbin   3   0.1359 0.05838 30 2.33 0.0268 0.05 0.01672 0.2552
hospbin   6   0.01850 0.05635 30 0.33 0.7449 0.05 -0.09658 0.1336
hospbin   9   0.02577 0.06993 30 0.37 0.7151 0.05 -0.1170 0.1686
age_group     1 0.1625 0.05444 30 2.99 0.0056 0.05 0.05133 0.2737
age_group     2 0.01154 0.08433 30 0.14 0.8921 0.05 -0.1607 0.1838
age_group     3 0.006170 0.03738 30 0.17 0.8700 0.05 -0.07016 0.08250
hospbin*age_group   3 1 0.3992 0.1033 30 3.86 0.0006 0.05 0.1883 0.6101
hospbin*age_group   3 2 0.003185 0.1265 30 0.03 0.9801 0.05 -0.2552 0.2615
hospbin*age_group   3 3 0.005438 0.06325 30 0.09 0.9321 0.05 -0.1237 0.1346
hospbin*age_group   6 1 0.02222 0.08945 30 0.25 0.8055 0.05 -0.1605 0.2049
hospbin*age_group   6 2 0.02866 0.1265 30 0.23 0.8223 0.05 -0.2297 0.2870
hospbin*age_group   6 3 0.004631 0.06762 30 0.07 0.9459 0.05 -0.1335 0.1427
hospbin*age_group   9 1 0.06609 0.08945 30 0.74 0.4657 0.05 -0.1166 0.2488
hospbin*age_group   9 2 0.002774 0.1789 30 0.02 0.9877 0.05 -0.3626 0.3681
hospbin*age_group   9 3 0.008441 0.06325 30 0.13 0.8947 0.05 -0.1207 0.1376
sample_type2 A     0.09231 0.06148 30 1.50 0.1437 0.05 -0.03325 0.2179
sample_type2 B     0.03730 0.01977 30 1.89 0.0689 0.05 -0.00308 0.07767
sample_type2 C     0.05060 0.02621 30 1.93 0.0630 0.05 -0.00292 0.1041
hospbin*sample_type2 A 3   0.2315 0.1005 30 2.30 0.0284 0.05 0.02617 0.4368
hospbin*sample_type2 B 3   0.07504 0.03232 30 2.32 0.0272 0.05 0.009032 0.1411
hospbin*sample_type2 C 3   0.1013 0.04285 30 2.36 0.0247 0.05 0.01380 0.1888
hospbin*sample_type2 A 6   0.01599 0.09703 30 0.16 0.8702 0.05 -0.1822 0.2142
hospbin*sample_type2 B 6   0.01402 0.03120 30 0.45 0.6565 0.05 -0.04970 0.07773
hospbin*sample_type2 C 6   0.02550 0.04136 30 0.62 0.5422 0.05 -0.05897 0.1100
hospbin*sample_type2 A 9   0.02948 0.1204 30 0.24 0.8083 0.05 -0.2164 0.2754
hospbin*sample_type2 B 9   0.02283 0.03872 30 0.59 0.5598 0.05 -0.05624 0.1019
hospbin*sample_type2 C 9   0.02499 0.05133 30 0.49 0.6298 0.05 -0.07983 0.1298
age_group*sample_typ A   1 0.2628 0.09374 30 2.80 0.0088 0.05 0.07139 0.4543
age_group*sample_typ B   1 0.09956 0.03014 30 3.30 0.0025 0.05 0.03800 0.1611
age_group*sample_typ C   1 0.1251 0.03996 30 3.13 0.0039 0.05 0.04351 0.2067
age_group*sample_typ A   2 0.009572 0.1452 30 0.07 0.9479 0.05 -0.2870 0.3062
age_group*sample_typ B   2 0.006997 0.04669 30 0.15 0.8819 0.05 -0.08837 0.1024
age_group*sample_typ C   2 0.01805 0.06190 30 0.29 0.7726 0.05 -0.1084 0.1445
age_group*sample_typ A   3 0.004537 0.06436 30 0.07 0.9443 0.05 -0.1269 0.1360
age_group*sample_typ B   3 0.005334 0.02069 30 0.26 0.7983 0.05 -0.03693 0.04760
age_group*sample_typ C   3 0.008639 0.02744 30 0.31 0.7550 0.05 -0.04739 0.06467
hospbi*age_gr*sample A 3 1 0.6877 0.1779 30 3.87 0.0006 0.05 0.3245 1.0510
hospbi*age_gr*sample B 3 1 0.2162 0.05719 30 3.78 0.0007 0.05 0.09942 0.3330
hospbi*age_gr*sample C 3 1 0.2937 0.07582 30 3.87 0.0005 0.05 0.1388 0.4485
hospbi*age_gr*sample A 3 2 0.002670 0.2178 30 0.01 0.9903 0.05 -0.4422 0.4475
hospbi*age_gr*sample B 3 2 0.003685 0.07004 30 0.05 0.9584 0.05 -0.1394 0.1467
hospbi*age_gr*sample C 3 2 0.003199 0.09286 30 0.03 0.9727 0.05 -0.1864 0.1928
hospbi*age_gr*sample A 3 3 0.004011 0.1089 30 0.04 0.9709 0.05 -0.2184 0.2265
hospbi*age_gr*sample B 3 3 0.005232 0.03502 30 0.15 0.8822 0.05 -0.06629 0.07675
hospbi*age_gr*sample C 3 3 0.007070 0.04643 30 0.15 0.8800 0.05 -0.08775 0.1019
hospbi*age_gr*sample A 6 1 0.02152 0.1540 30 0.14 0.8898 0.05 -0.2931 0.3361
hospbi*age_gr*sample B 6 1 0.02265 0.04953 30 0.46 0.6507 0.05 -0.07850 0.1238
hospbi*age_gr*sample C 6 1 0.02248 0.06566 30 0.34 0.7344 0.05 -0.1116 0.1566
hospbi*age_gr*sample A 6 2 0.02289 0.2178 30 0.11 0.9170 0.05 -0.4220 0.4678
hospbi*age_gr*sample B 6 2 0.01580 0.07004 30 0.23 0.8231 0.05 -0.1272 0.1588
hospbi*age_gr*sample C 6 2 0.04729 0.09286 30 0.51 0.6143 0.05 -0.1423 0.2369
hospbi*age_gr*sample A 6 3 0.003565 0.1164 30 0.03 0.9758 0.05 -0.2342 0.2414
hospbi*age_gr*sample B 6 3 0.003602 0.03744 30 0.10 0.9240 0.05 -0.07286 0.08006
hospbi*age_gr*sample C 6 3 0.006727 0.04963 30 0.14 0.8931 0.05 -0.09464 0.1081
hospbi*age_gr*sample A 9 1 0.07925 0.1540 30 0.51 0.6107 0.05 -0.2353 0.3938
hospbi*age_gr*sample B 9 1 0.05981 0.04953 30 1.21 0.2366 0.05 -0.04133 0.1610
hospbi*age_gr*sample C 9 1 0.05921 0.06566 30 0.90 0.3744 0.05 -0.07489 0.1933
hospbi*age_gr*sample A 9 2 0.003155 0.3081 30 0.01 0.9919 0.05 -0.6260 0.6323
hospbi*age_gr*sample B 9 2 0.001509 0.09905 30 0.02 0.9879 0.05 -0.2008 0.2038
hospbi*age_gr*sample C 9 2 0.003658 0.1313 30 0.03 0.9780 0.05 -0.2645 0.2718
hospbi*age_gr*sample A 9 3 0.006034 0.1089 30 0.06 0.9562 0.05 -0.2164 0.2285
hospbi*age_gr*sample B 9 3 0.007169 0.03502 30 0.20 0.8392 0.05 -0.06435 0.07869
hospbi*age_gr*sample C 9 3 0.01212 0.04643 30 0.26 0.7958 0.05 -0.08270 0.1069
Differences of Least Squares Means
Effect sample_type2 hospbin age_group _sample_type2 hospbin _age_group Estimate Standard
Error
DF t Value Pr > |t| Adjustment Adj P Alpha Lower Upper Adj Lower Adj Upper
hospbin   3     6   0.1174 0.08114 30 1.45 0.1581 Tukey-Kramer 0.3302 0.05 -0.04826 0.2831 -0.08258 0.3175
hospbin   3     9   0.1102 0.09109 30 1.21 0.2359 Tukey-Kramer 0.4569 0.05 -0.07586 0.2962 -0.1144 0.3347
hospbin   6     9   -0.00727 0.08980 30 -0.08 0.9361 Tukey-Kramer 0.9964 0.05 -0.1907 0.1761 -0.2287 0.2141
age_group     1     2 0.1510 0.1004 30 1.50 0.1430 Tukey-Kramer 0.3034 0.05 -0.05403 0.3560 -0.09649 0.3984
age_group     1     3 0.1563 0.06603 30 2.37 0.0246 Tukey-Kramer 0.0618 0.05 0.02147 0.2912 -0.00646 0.3191
age_group     2     3 0.005369 0.09225 30 0.06 0.9540 Tukey-Kramer 0.9981 0.05 -0.1830 0.1938 -0.2220 0.2328
hospbin*age_group   3 1   3 2 0.3960 0.1633 30 2.42 0.0215 Tukey-Kramer 0.3075 0.05 0.06249 0.7296 -0.1490 0.9411
hospbin*age_group   3 1   3 3 0.3938 0.1211 30 3.25 0.0028 Tukey-Kramer 0.0608 0.05 0.1464 0.6411 -0.01046 0.7980
hospbin*age_group   3 1   6 1 0.3770 0.1366 30 2.76 0.0098 Tukey-Kramer 0.1702 0.05 0.09794 0.6560 -0.07904 0.8330
hospbin*age_group   3 1   6 2 0.3705 0.1633 30 2.27 0.0306 Tukey-Kramer 0.3908 0.05 0.03702 0.7041 -0.1745 0.9156
hospbin*age_group   3 1   6 3 0.3946 0.1235 30 3.20 0.0033 Tukey-Kramer 0.0688 0.05 0.1425 0.6467 -0.01745 0.8066
hospbin*age_group   3 1   9 1 0.3331 0.1366 30 2.44 0.0209 Tukey-Kramer 0.3011 0.05 0.05406 0.6122 -0.1229 0.7891
hospbin*age_group   3 1   9 2 0.3964 0.2066 30 1.92 0.0645 Tukey-Kramer 0.6067 0.05 -0.02545 0.8183 -0.2930 1.0859
hospbin*age_group   3 1   9 3 0.3908 0.1211 30 3.23 0.0030 Tukey-Kramer 0.0643 0.05 0.1434 0.6381 -0.01346 0.7950
hospbin*age_group   3 2   3 3 -0.00225 0.1414 30 -0.02 0.9874 Tukey-Kramer 1.0000 0.05 -0.2911 0.2866 -0.4743 0.4698
hospbin*age_group   3 2   6 1 -0.01903 0.1549 30 -0.12 0.9031 Tukey-Kramer 1.0000 0.05 -0.3354 0.2974 -0.5361 0.4981
hospbin*age_group   3 2   6 2 -0.02547 0.1789 30 -0.14 0.8877 Tukey-Kramer 1.0000 0.05 -0.3908 0.3399 -0.6226 0.5716
hospbin*age_group   3 2   6 3 -0.00145 0.1434 30 -0.01 0.9920 Tukey-Kramer 1.0000 0.05 -0.2944 0.2915 -0.4802 0.4773
hospbin*age_group   3 2   9 1 -0.06291 0.1549 30 -0.41 0.6876 Tukey-Kramer 1.0000 0.05 -0.3793 0.2535 -0.5800 0.4542
hospbin*age_group   3 2   9 2 0.000411 0.2191 30 0.00 0.9985 Tukey-Kramer 1.0000 0.05 -0.4471 0.4479 -0.7309 0.7317
hospbin*age_group   3 2   9 3 -0.00526 0.1414 30 -0.04 0.9706 Tukey-Kramer 1.0000 0.05 -0.2941 0.2836 -0.4773 0.4668
hospbin*age_group   3 3   6 1 -0.01678 0.1096 30 -0.15 0.8793 Tukey-Kramer 1.0000 0.05 -0.2405 0.2070 -0.3824 0.3489
hospbin*age_group   3 3   6 2 -0.02322 0.1414 30 -0.16 0.8707 Tukey-Kramer 1.0000 0.05 -0.3121 0.2656 -0.4953 0.4488
hospbin*age_group   3 3   6 3 0.000807 0.09259 30 0.01 0.9931 Tukey-Kramer 1.0000 0.05 -0.1883 0.1899 -0.3082 0.3098
hospbin*age_group   3 3   9 1 -0.06065 0.1096 30 -0.55 0.5839 Tukey-Kramer 0.9997 0.05 -0.2844 0.1631 -0.4263 0.3050
hospbin*age_group   3 3   9 2 0.002664 0.1898 30 0.01 0.9889 Tukey-Kramer 1.0000 0.05 -0.3849 0.3902 -0.6306 0.6360
hospbin*age_group   3 3   9 3 -0.00300 0.08945 30 -0.03 0.9734 Tukey-Kramer 1.0000 0.05 -0.1857 0.1797 -0.3015 0.2955
hospbin*age_group   6 1   6 2 -0.00644 0.1549 30 -0.04 0.9671 Tukey-Kramer 1.0000 0.05 -0.3229 0.3100 -0.5235 0.5106
hospbin*age_group   6 1   6 3 0.01759 0.1121 30 0.16 0.8764 Tukey-Kramer 1.0000 0.05 -0.2114 0.2466 -0.3567 0.3918
hospbin*age_group   6 1   9 1 -0.04387 0.1265 30 -0.35 0.7311 Tukey-Kramer 1.0000 0.05 -0.3022 0.2145 -0.4661 0.3783
hospbin*age_group   6 1   9 2 0.01944 0.2000 30 0.10 0.9232 Tukey-Kramer 1.0000 0.05 -0.3890 0.4279 -0.6481 0.6870
hospbin*age_group   6 1   9 3 0.01378 0.1096 30 0.13 0.9008 Tukey-Kramer 1.0000 0.05 -0.2100 0.2375 -0.3519 0.3794
hospbin*age_group   6 2   6 3 0.02403 0.1434 30 0.17 0.8681 Tukey-Kramer 1.0000 0.05 -0.2689 0.3170 -0.4547 0.5028
hospbin*age_group   6 2   9 1 -0.03743 0.1549 30 -0.24 0.8107 Tukey-Kramer 1.0000 0.05 -0.3538 0.2790 -0.5545 0.4797
hospbin*age_group   6 2   9 2 0.02589 0.2191 30 0.12 0.9067 Tukey-Kramer 1.0000 0.05 -0.4216 0.4734 -0.7054 0.7572
hospbin*age_group   6 2   9 3 0.02022 0.1414 30 0.14 0.8873 Tukey-Kramer 1.0000 0.05 -0.2686 0.3091 -0.4518 0.4923
hospbin*age_group   6 3   9 1 -0.06146 0.1121 30 -0.55 0.5877 Tukey-Kramer 0.9997 0.05 -0.2905 0.1675 -0.4357 0.3128
hospbin*age_group   6 3   9 2 0.001857 0.1913 30 0.01 0.9923 Tukey-Kramer 1.0000 0.05 -0.3887 0.3924 -0.6364 0.6402
hospbin*age_group   6 3   9 3 -0.00381 0.09259 30 -0.04 0.9674 Tukey-Kramer 1.0000 0.05 -0.1929 0.1853 -0.3128 0.3052
hospbin*age_group   9 1   9 2 0.06332 0.2000 30 0.32 0.7538 Tukey-Kramer 1.0000 0.05 -0.3452 0.4718 -0.6042 0.7309
hospbin*age_group   9 1   9 3 0.05765 0.1096 30 0.53 0.6026 Tukey-Kramer 0.9998 0.05 -0.1661 0.2814 -0.3080 0.4233
hospbin*age_group   9 2   9 3 -0.00567 0.1898 30 -0.03 0.9764 Tukey-Kramer 1.0000 0.05 -0.3932 0.3819 -0.6390 0.6276
sample_type2 A     B     0.05502 0.04223 30 1.30 0.2026 Tukey-Kramer 0.4047 0.05 -0.03123 0.1413 -0.04909 0.1591
sample_type2 A     C     0.04171 0.03566 30 1.17 0.2513 Tukey-Kramer 0.4800 0.05 -0.03112 0.1145 -0.04620 0.1296
sample_type2 B     C     -0.01331 0.006708 30 -1.98 0.0565 Tukey-Kramer 0.1337 0.05 -0.02701 0.000394 -0.02984 0.003232
hospbin*sample_type2 A 3   B 3   0.1564 0.06905 30 2.27 0.0309 Tukey-Kramer 0.3928 0.05 0.01541 0.2974 -0.07403 0.3869
hospbin*sample_type2 A 3   C 3   0.1302 0.05831 30 2.23 0.0332 Tukey-Kramer 0.4118 0.05 0.01108 0.2492 -0.06444 0.3248
hospbin*sample_type2 A 3   A 6   0.2155 0.1397 30 1.54 0.1335 Tukey-Kramer 0.8267 0.05 -0.06986 0.5008 -0.2508 0.6818
hospbin*sample_type2 A 3   B 6   0.2175 0.1053 30 2.07 0.0476 Tukey-Kramer 0.5132 0.05 0.002494 0.4324 -0.1338 0.5687
hospbin*sample_type2 A 3   C 6   0.2060 0.1087 30 1.89 0.0678 Tukey-Kramer 0.6222 0.05 -0.01603 0.4280 -0.1568 0.5688
hospbin*sample_type2 A 3   A 9   0.2020 0.1569 30 1.29 0.2077 Tukey-Kramer 0.9273 0.05 -0.1184 0.5223 -0.3215 0.7255
hospbin*sample_type2 A 3   B 9   0.2086 0.1077 30 1.94 0.0622 Tukey-Kramer 0.5954 0.05 -0.01136 0.4286 -0.1509 0.5682
hospbin*sample_type2 A 3   C 9   0.2065 0.1129 30 1.83 0.0773 Tukey-Kramer 0.6636 0.05 -0.02404 0.4370 -0.1702 0.5832
hospbin*sample_type2 B 3   C 3   -0.02627 0.01097 30 -2.39 0.0231 Tukey-Kramer 0.3226 0.05 -0.04867 -0.00387 -0.06288 0.01034
hospbin*sample_type2 B 3   A 6   0.05905 0.1023 30 0.58 0.5680 Tukey-Kramer 0.9996 0.05 -0.1498 0.2679 -0.2823 0.4004
hospbin*sample_type2 B 3   B 6   0.06103 0.04492 30 1.36 0.1844 Tukey-Kramer 0.9044 0.05 -0.03072 0.1528 -0.08890 0.2110
hospbin*sample_type2 B 3   C 6   0.04954 0.05249 30 0.94 0.3528 Tukey-Kramer 0.9882 0.05 -0.05766 0.1567 -0.1257 0.2247
hospbin*sample_type2 B 3   A 9   0.04556 0.1247 30 0.37 0.7173 Tukey-Kramer 1.0000 0.05 -0.2091 0.3002 -0.3705 0.4617
hospbin*sample_type2 B 3   B 9   0.05221 0.05044 30 1.04 0.3088 Tukey-Kramer 0.9789 0.05 -0.05079 0.1552 -0.1161 0.2205
hospbin*sample_type2 B 3   C 9   0.05005 0.06066 30 0.83 0.4158 Tukey-Kramer 0.9951 0.05 -0.07383 0.1739 -0.1524 0.2525
hospbin*sample_type2 C 3   A 6   0.08532 0.1061 30 0.80 0.4275 Tukey-Kramer 0.9959 0.05 -0.1313 0.3020 -0.2687 0.4393
hospbin*sample_type2 C 3   B 6   0.08730 0.05301 30 1.65 0.1100 Tukey-Kramer 0.7720 0.05 -0.02095 0.1955 -0.08961 0.2642
hospbin*sample_type2 C 3   C 6   0.07581 0.05956 30 1.27 0.2128 Tukey-Kramer 0.9316 0.05 -0.04582 0.1974 -0.1230 0.2746
hospbin*sample_type2 C 3   A 9   0.07183 0.1278 30 0.56 0.5783 Tukey-Kramer 0.9997 0.05 -0.1892 0.3329 -0.3547 0.4984
hospbin*sample_type2 C 3   B 9   0.07848 0.05775 30 1.36 0.1843 Tukey-Kramer 0.9042 0.05 -0.03946 0.1964 -0.1143 0.2712
hospbin*sample_type2 C 3   C 9   0.07632 0.06686 30 1.14 0.2627 Tukey-Kramer 0.9625 0.05 -0.06024 0.2129 -0.1468 0.2995
hospbin*sample_type2 A 6   B 6   0.001975 0.06665 30 0.03 0.9766 Tukey-Kramer 1.0000 0.05 -0.1341 0.1381 -0.2205 0.2244
hospbin*sample_type2 A 6   C 6   -0.00951 0.05628 30 -0.17 0.8670 Tukey-Kramer 1.0000 0.05 -0.1244 0.1054 -0.1973 0.1783
hospbin*sample_type2 A 6   A 9   -0.01349 0.1546 30 -0.09 0.9311 Tukey-Kramer 1.0000 0.05 -0.3293 0.3023 -0.5296 0.5026
hospbin*sample_type2 A 6   B 9   -0.00684 0.1045 30 -0.07 0.9482 Tukey-Kramer 1.0000 0.05 -0.2202 0.2065 -0.3555 0.3418
hospbin*sample_type2 A 6   C 9   -0.00900 0.1098 30 -0.08 0.9352 Tukey-Kramer 1.0000 0.05 -0.2332 0.2152 -0.3754 0.3574
hospbin*sample_type2 B 6   C 6   -0.01148 0.01059 30 -1.08 0.2867 Tukey-Kramer 0.9721 0.05 -0.03311 0.01014 -0.04682 0.02385
hospbin*sample_type2 B 6   A 9   -0.01546 0.1244 30 -0.12 0.9019 Tukey-Kramer 1.0000 0.05 -0.2695 0.2386 -0.4306 0.3997
hospbin*sample_type2 B 6   B 9   -0.00881 0.04972 30 -0.18 0.8605 Tukey-Kramer 1.0000 0.05 -0.1104 0.09273 -0.1748 0.1571
hospbin*sample_type2 B 6   C 9   -0.01098 0.06007 30 -0.18 0.8562 Tukey-Kramer 1.0000 0.05 -0.1337 0.1117 -0.2115 0.1895
hospbin*sample_type2 C 6   A 9   -0.00398 0.1273 30 -0.03 0.9753 Tukey-Kramer 1.0000 0.05 -0.2640 0.2560 -0.4289 0.4209
hospbin*sample_type2 C 6   B 9   0.002670 0.05665 30 0.05 0.9627 Tukey-Kramer 1.0000 0.05 -0.1130 0.1184 -0.1864 0.1918
hospbin*sample_type2 C 6   C 9   0.000506 0.06592 30 0.01 0.9939 Tukey-Kramer 1.0000 0.05 -0.1341 0.1351 -0.2195 0.2205
hospbin*sample_type2 A 9   B 9   0.006649 0.08271 30 0.08 0.9365 Tukey-Kramer 1.0000 0.05 -0.1623 0.1756 -0.2694 0.2827
hospbin*sample_type2 A 9   C 9   0.004485 0.06984 30 0.06 0.9492 Tukey-Kramer 1.0000 0.05 -0.1381 0.1471 -0.2286 0.2376
hospbin*sample_type2 B 9   C 9   -0.00216 0.01314 30 -0.16 0.8703 Tukey-Kramer 1.0000 0.05 -0.02900 0.02467 -0.04601 0.04169
age_group*sample_typ A   1 B   1 0.1633 0.06439 30 2.54 0.0167 Tukey-Kramer 0.2556 0.05 0.03178 0.2948 -0.05162 0.3782
age_group*sample_typ A   1 C   1 0.1377 0.05437 30 2.53 0.0168 Tukey-Kramer 0.2568 0.05 0.02667 0.2488 -0.04375 0.3192
age_group*sample_typ A   1 A   2 0.2533 0.1729 30 1.47 0.1533 Tukey-Kramer 0.8624 0.05 -0.09975 0.6063 -0.3236 0.8302
age_group*sample_typ A   1 B   2 0.2558 0.1047 30 2.44 0.0207 Tukey-Kramer 0.2987 0.05 0.04196 0.4697 -0.09369 0.6054
age_group*sample_typ A   1 C   2 0.2448 0.1123 30 2.18 0.0373 Tukey-Kramer 0.4434 0.05 0.01536 0.4742 -0.1301 0.6197
age_group*sample_typ A   1 A   3 0.2583 0.1137 30 2.27 0.0305 Tukey-Kramer 0.3893 0.05 0.02607 0.4905 -0.1212 0.6378
age_group*sample_typ A   1 B   3 0.2575 0.09600 30 2.68 0.0118 Tukey-Kramer 0.1967 0.05 0.06144 0.4536 -0.06290 0.5779
age_group*sample_typ A   1 C   3 0.2542 0.09767 30 2.60 0.0142 Tukey-Kramer 0.2274 0.05 0.05472 0.4537 -0.07179 0.5802
age_group*sample_typ B   1 C   1 -0.02556 0.01023 30 -2.50 0.0182 Tukey-Kramer 0.2721 0.05 -0.04645 -0.00467 -0.05970 0.008576
age_group*sample_typ B   1 A   2 0.08999 0.1483 30 0.61 0.5486 Tukey-Kramer 0.9994 0.05 -0.2129 0.3929 -0.4050 0.5850
age_group*sample_typ B   1 B   2 0.09256 0.05558 30 1.67 0.1062 Tukey-Kramer 0.7616 0.05 -0.02094 0.2061 -0.09293 0.2781
age_group*sample_typ B   1 C   2 0.08151 0.06885 30 1.18 0.2458 Tukey-Kramer 0.9539 0.05 -0.05911 0.2221 -0.1483 0.3113
age_group*sample_typ B   1 A   3 0.09502 0.07107 30 1.34 0.1913 Tukey-Kramer 0.9117 0.05 -0.05012 0.2402 -0.1422 0.3322
age_group*sample_typ B   1 B   3 0.09422 0.03656 30 2.58 0.0151 Tukey-Kramer 0.2378 0.05 0.01956 0.1689 -0.02780 0.2162
age_group*sample_typ B   1 C   3 0.09092 0.04076 30 2.23 0.0333 Tukey-Kramer 0.4128 0.05 0.007681 0.1742 -0.04511 0.2269
age_group*sample_typ C   1 A   2 0.1155 0.1506 30 0.77 0.4490 Tukey-Kramer 0.9970 0.05 -0.1921 0.4232 -0.3871 0.6182
age_group*sample_typ C   1 B   2 0.1181 0.06146 30 1.92 0.0641 Tukey-Kramer 0.6049 0.05 -0.00739 0.2436 -0.08699 0.3232
age_group*sample_typ C   1 C   2 0.1071 0.07368 30 1.45 0.1566 Tukey-Kramer 0.8675 0.05 -0.04341 0.2575 -0.1388 0.3530
age_group*sample_typ C   1 A   3 0.1206 0.07576 30 1.59 0.1219 Tukey-Kramer 0.8017 0.05 -0.03414 0.2753 -0.1323 0.3734
age_group*sample_typ C   1 B   3 0.1198 0.04500 30 2.66 0.0124 Tukey-Kramer 0.2042 0.05 0.02788 0.2117 -0.03040 0.2700
age_group*sample_typ C   1 C   3 0.1165 0.04847 30 2.40 0.0226 Tukey-Kramer 0.3185 0.05 0.01749 0.2155 -0.04529 0.2783
age_group*sample_typ A   2 B   2 0.002575 0.09975 30 0.03 0.9796 Tukey-Kramer 1.0000 0.05 -0.2011 0.2063 -0.3303 0.3355
age_group*sample_typ A   2 C   2 -0.00848 0.08423 30 -0.10 0.9205 Tukey-Kramer 1.0000 0.05 -0.1805 0.1635 -0.2896 0.2726
age_group*sample_typ A   2 A   3 0.005035 0.1588 30 0.03 0.9749 Tukey-Kramer 1.0000 0.05 -0.3194 0.3294 -0.5251 0.5352
age_group*sample_typ A   2 B   3 0.004237 0.1467 30 0.03 0.9771 Tukey-Kramer 1.0000 0.05 -0.2953 0.3038 -0.4853 0.4938
age_group*sample_typ A   2 C   3 0.000933 0.1478 30 0.01 0.9950 Tukey-Kramer 1.0000 0.05 -0.3009 0.3028 -0.4923 0.4942
age_group*sample_typ B   2 C   2 -0.01105 0.01585 30 -0.70 0.4908 Tukey-Kramer 0.9985 0.05 -0.04341 0.02131 -0.06394 0.04183
age_group*sample_typ B   2 A   3 0.002460 0.07952 30 0.03 0.9755 Tukey-Kramer 1.0000 0.05 -0.1599 0.1649 -0.2629 0.2678
age_group*sample_typ B   2 B   3 0.001662 0.05107 30 0.03 0.9743 Tukey-Kramer 1.0000 0.05 -0.1026 0.1060 -0.1688 0.1721
age_group*sample_typ B   2 C   3 -0.00164 0.05416 30 -0.03 0.9760 Tukey-Kramer 1.0000 0.05 -0.1122 0.1090 -0.1824 0.1791
age_group*sample_typ C   2 A   3 0.01351 0.08930 30 0.15 0.8807 Tukey-Kramer 1.0000 0.05 -0.1689 0.1959 -0.2845 0.3116
age_group*sample_typ C   2 B   3 0.01271 0.06527 30 0.19 0.8469 Tukey-Kramer 1.0000 0.05 -0.1206 0.1460 -0.2051 0.2306
age_group*sample_typ C   2 C   3 0.009410 0.06771 30 0.14 0.8904 Tukey-Kramer 1.0000 0.05 -0.1289 0.1477 -0.2166 0.2354
age_group*sample_typ A   3 B   3 -0.00080 0.04421 30 -0.02 0.9857 Tukey-Kramer 1.0000 0.05 -0.09109 0.08949 -0.1483 0.1468
age_group*sample_typ A   3 C   3 -0.00410 0.03733 30 -0.11 0.9132 Tukey-Kramer 1.0000 0.05 -0.08034 0.07214 -0.1287 0.1205
age_group*sample_typ B   3 C   3 -0.00330 0.007023 30 -0.47 0.6414 Tukey-Kramer 0.9999 0.05 -0.01765 0.01104 -0.02674 0.02013
hospbi*age_gr*sample A 3 1 B 3 1 0.4715 0.1222 30 3.86 0.0006 Tukey-Kramer 0.0785 0.05 0.2220 0.7210 -0.02448 0.9675
hospbi*age_gr*sample A 3 1 C 3 1 0.3941 0.1032 30 3.82 0.0006 Tukey-Kramer 0.0856 0.05 0.1834 0.6047 -0.02476 0.8129
hospbi*age_gr*sample A 3 1 A 3 2 0.6851 0.2812 30 2.44 0.0210 Tukey-Kramer 0.7536 0.05 0.1107 1.2594 -0.4567 1.8268
hospbi*age_gr*sample A 3 1 B 3 2 0.6840 0.1912 30 3.58 0.0012 Tukey-Kramer 0.1420 0.05 0.2937 1.0744 -0.09203 1.4601
hospbi*age_gr*sample A 3 1 C 3 2 0.6845 0.2006 30 3.41 0.0019 Tukey-Kramer 0.1966 0.05 0.2748 1.0943 -0.1301 1.4991
hospbi*age_gr*sample A 3 1 A 3 3 0.6837 0.2086 30 3.28 0.0026 Tukey-Kramer 0.2509 0.05 0.2578 1.1097 -0.1630 1.5305
hospbi*age_gr*sample A 3 1 B 3 3 0.6825 0.1813 30 3.76 0.0007 Tukey-Kramer 0.0964 0.05 0.3123 1.0527 -0.05347 1.4185
hospbi*age_gr*sample A 3 1 C 3 3 0.6807 0.1838 30 3.70 0.0009 Tukey-Kramer 0.1100 0.05 0.3053 1.0561 -0.06564 1.4270
hospbi*age_gr*sample A 3 1 A 6 1 0.6662 0.2353 30 2.83 0.0082 Tukey-Kramer 0.4993 0.05 0.1857 1.1467 -0.2890 1.6215
hospbi*age_gr*sample A 3 1 B 6 1 0.6651 0.1846 30 3.60 0.0011 Tukey-Kramer 0.1354 0.05 0.2880 1.0421 -0.08450 1.4147
hospbi*age_gr*sample A 3 1 C 6 1 0.6653 0.1896 30 3.51 0.0014 Tukey-Kramer 0.1631 0.05 0.2780 1.0525 -0.1045 1.4350
hospbi*age_gr*sample A 3 1 A 6 2 0.6648 0.2812 30 2.36 0.0247 Tukey-Kramer 0.7946 0.05 0.09051 1.2392 -0.4769 1.8066
hospbi*age_gr*sample A 3 1 B 6 2 0.6719 0.1912 30 3.52 0.0014 Tukey-Kramer 0.1611 0.05 0.2815 1.0623 -0.1041 1.4480
hospbi*age_gr*sample A 3 1 C 6 2 0.6404 0.2006 30 3.19 0.0033 Tukey-Kramer 0.2913 0.05 0.2307 1.0502 -0.1742 1.4550
hospbi*age_gr*sample A 3 1 A 6 3 0.6842 0.2126 30 3.22 0.0031 Tukey-Kramer 0.2785 0.05 0.2500 1.1183 -0.1789 1.5473
hospbi*age_gr*sample A 3 1 B 6 3 0.6841 0.1818 30 3.76 0.0007 Tukey-Kramer 0.0966 0.05 0.3129 1.0553 -0.05380 1.4221
hospbi*age_gr*sample A 3 1 C 6 3 0.6810 0.1847 30 3.69 0.0009 Tukey-Kramer 0.1134 0.05 0.3039 1.0581 -0.06869 1.4307
hospbi*age_gr*sample A 3 1 A 9 1 0.6085 0.2353 30 2.59 0.0148 Tukey-Kramer 0.6601 0.05 0.1280 1.0890 -0.3468 1.5637
hospbi*age_gr*sample A 3 1 B 9 1 0.6279 0.1846 30 3.40 0.0019 Tukey-Kramer 0.2007 0.05 0.2509 1.0050 -0.1217 1.3775
hospbi*age_gr*sample A 3 1 C 9 1 0.6285 0.1896 30 3.32 0.0024 Tukey-Kramer 0.2350 0.05 0.2413 1.0157 -0.1412 1.3983
hospbi*age_gr*sample A 3 1 A 9 2 0.6846 0.3557 30 1.92 0.0638 Tukey-Kramer 0.9604 0.05 -0.04190 1.4111 -0.7596 2.1288
hospbi*age_gr*sample A 3 1 B 9 2 0.6862 0.2036 30 3.37 0.0021 Tukey-Kramer 0.2123 0.05 0.2705 1.1020 -0.1403 1.5128
hospbi*age_gr*sample A 3 1 C 9 2 0.6841 0.2211 30 3.09 0.0042 Tukey-Kramer 0.3418 0.05 0.2326 1.1356 -0.2135 1.5817
hospbi*age_gr*sample A 3 1 A 9 3 0.6817 0.2086 30 3.27 0.0027 Tukey-Kramer 0.2553 0.05 0.2558 1.1076 -0.1650 1.5284
hospbi*age_gr*sample A 3 1 B 9 3 0.6806 0.1813 30 3.75 0.0007 Tukey-Kramer 0.0986 0.05 0.3103 1.0508 -0.05541 1.4165
hospbi*age_gr*sample A 3 1 C 9 3 0.6756 0.1838 30 3.68 0.0009 Tukey-Kramer 0.1165 0.05 0.3002 1.0510 -0.07069 1.4219
hospbi*age_gr*sample B 3 1 C 3 1 -0.07746 0.01941 30 -3.99 0.0004 Tukey-Kramer 0.0585 0.05 -0.1171 -0.03782 -0.1562 0.001334
hospbi*age_gr*sample B 3 1 A 3 2 0.2135 0.2252 30 0.95 0.3506 Tukey-Kramer 1.0000 0.05 -0.2464 0.6735 -0.7008 1.1279
hospbi*age_gr*sample B 3 1 B 3 2 0.2125 0.09042 30 2.35 0.0255 Tukey-Kramer 0.8021 0.05 0.02786 0.3972 -0.1546 0.5796
hospbi*age_gr*sample B 3 1 C 3 2 0.2130 0.1091 30 1.95 0.0602 Tukey-Kramer 0.9543 0.05 -0.00970 0.4357 -0.2297 0.6558
hospbi*age_gr*sample B 3 1 A 3 3 0.2122 0.1230 30 1.72 0.0948 Tukey-Kramer 0.9876 0.05 -0.03904 0.4634 -0.2872 0.7117
hospbi*age_gr*sample B 3 1 B 3 3 0.2110 0.06706 30 3.15 0.0037 Tukey-Kramer 0.3143 0.05 0.07403 0.3479 -0.06128 0.4832
hospbi*age_gr*sample B 3 1 C 3 3 0.2091 0.07366 30 2.84 0.0080 Tukey-Kramer 0.4943 0.05 0.05871 0.3596 -0.08992 0.5082
hospbi*age_gr*sample B 3 1 A 6 1 0.1947 0.1643 30 1.18 0.2453 Tukey-Kramer 0.9999 0.05 -0.1409 0.5303 -0.4724 0.8618
hospbi*age_gr*sample B 3 1 B 6 1 0.1936 0.07565 30 2.56 0.0158 Tukey-Kramer 0.6778 0.05 0.03906 0.3481 -0.1136 0.5007
hospbi*age_gr*sample B 3 1 C 6 1 0.1937 0.08707 30 2.22 0.0338 Tukey-Kramer 0.8641 0.05 0.01590 0.3716 -0.1598 0.5472
hospbi*age_gr*sample B 3 1 A 6 2 0.1933 0.2252 30 0.86 0.3975 Tukey-Kramer 1.0000 0.05 -0.2666 0.6533 -0.7210 1.1077
hospbi*age_gr*sample B 3 1 B 6 2 0.2004 0.09042 30 2.22 0.0344 Tukey-Kramer 0.8678 0.05 0.01575 0.3851 -0.1667 0.5675
hospbi*age_gr*sample B 3 1 C 6 2 0.1689 0.1091 30 1.55 0.1319 Tukey-Kramer 0.9968 0.05 -0.05380 0.3916 -0.2738 0.6117
hospbi*age_gr*sample B 3 1 A 6 3 0.2126 0.1297 30 1.64 0.1116 Tukey-Kramer 0.9933 0.05 -0.05228 0.4776 -0.3140 0.7393
hospbi*age_gr*sample B 3 1 B 6 3 0.2126 0.06835 30 3.11 0.0041 Tukey-Kramer 0.3331 0.05 0.07302 0.3522 -0.06490 0.4901
hospbi*age_gr*sample B 3 1 C 6 3 0.2095 0.07572 30 2.77 0.0096 Tukey-Kramer 0.5416 0.05 0.05484 0.3641 -0.09795 0.5169
hospbi*age_gr*sample B 3 1 A 9 1 0.1370 0.1643 30 0.83 0.4111 Tukey-Kramer 1.0000 0.05 -0.1986 0.4725 -0.5301 0.8040
hospbi*age_gr*sample B 3 1 B 9 1 0.1564 0.07565 30 2.07 0.0474 Tukey-Kramer 0.9240 0.05 0.001895 0.3109 -0.1507 0.4635
hospbi*age_gr*sample B 3 1 C 9 1 0.1570 0.08707 30 1.80 0.0814 Tukey-Kramer 0.9797 0.05 -0.02082 0.3348 -0.1965 0.5105
hospbi*age_gr*sample B 3 1 A 9 2 0.2131 0.3133 30 0.68 0.5017 Tukey-Kramer 1.0000 0.05 -0.4268 0.8530 -1.0590 1.4852
hospbi*age_gr*sample B 3 1 B 9 2 0.2147 0.1144 30 1.88 0.0703 Tukey-Kramer 0.9691 0.05 -0.01888 0.4483 -0.2497 0.6791
hospbi*age_gr*sample B 3 1 C 9 2 0.2126 0.1432 30 1.48 0.1482 Tukey-Kramer 0.9982 0.05 -0.07996 0.5051 -0.3690 0.7941
hospbi*age_gr*sample B 3 1 A 9 3 0.2102 0.1230 30 1.71 0.0979 Tukey-Kramer 0.9889 0.05 -0.04106 0.4614 -0.2893 0.7096
hospbi*age_gr*sample B 3 1 B 9 3 0.2090 0.06706 30 3.12 0.0040 Tukey-Kramer 0.3294 0.05 0.07209 0.3460 -0.06321 0.4813
hospbi*age_gr*sample B 3 1 C 9 3 0.2041 0.07366 30 2.77 0.0095 Tukey-Kramer 0.5388 0.05 0.05366 0.3545 -0.09497 0.5032
hospbi*age_gr*sample C 3 1 A 3 2 0.2910 0.2307 30 1.26 0.2168 Tukey-Kramer 0.9998 0.05 -0.1801 0.7621 -0.6454 1.2274
hospbi*age_gr*sample C 3 1 B 3 2 0.2900 0.1032 30 2.81 0.0087 Tukey-Kramer 0.5135 0.05 0.07919 0.5008 -0.1291 0.7090
hospbi*age_gr*sample C 3 1 C 3 2 0.2905 0.1199 30 2.42 0.0216 Tukey-Kramer 0.7612 0.05 0.04565 0.5353 -0.1962 0.7772
hospbi*age_gr*sample C 3 1 A 3 3 0.2897 0.1327 30 2.18 0.0370 Tukey-Kramer 0.8822 0.05 0.01863 0.5607 -0.2491 0.8284
hospbi*age_gr*sample C 3 1 B 3 3 0.2884 0.08351 30 3.45 0.0017 Tukey-Kramer 0.1815 0.05 0.1179 0.4590 -0.05063 0.6275
hospbi*age_gr*sample C 3 1 C 3 3 0.2866 0.08890 30 3.22 0.0030 Tukey-Kramer 0.2760 0.05 0.1050 0.4682 -0.07434 0.6475
hospbi*age_gr*sample C 3 1 A 6 1 0.2722 0.1717 30 1.59 0.1234 Tukey-Kramer 0.9956 0.05 -0.07847 0.6228 -0.4249 0.9692
hospbi*age_gr*sample C 3 1 B 6 1 0.2710 0.09056 30 2.99 0.0055 Tukey-Kramer 0.3993 0.05 0.08607 0.4560 -0.09665 0.6387
hospbi*age_gr*sample C 3 1 C 6 1 0.2712 0.1003 30 2.70 0.0112 Tukey-Kramer 0.5828 0.05 0.06635 0.4760 -0.1360 0.6784
hospbi*age_gr*sample C 3 1 A 6 2 0.2708 0.2307 30 1.17 0.2496 Tukey-Kramer 1.0000 0.05 -0.2003 0.7418 -0.6657 1.2072
hospbi*age_gr*sample C 3 1 B 6 2 0.2779 0.1032 30 2.69 0.0115 Tukey-Kramer 0.5906 0.05 0.06707 0.4887 -0.1412 0.6969
hospbi*age_gr*sample C 3 1 C 6 2 0.2464 0.1199 30 2.06 0.0486 Tukey-Kramer 0.9277 0.05 0.001557 0.4912 -0.2403 0.7331
hospbi*age_gr*sample C 3 1 A 6 3 0.2901 0.1389 30 2.09 0.0454 Tukey-Kramer 0.9173 0.05 0.006339 0.5739 -0.2740 0.8542
hospbi*age_gr*sample C 3 1 B 6 3 0.2901 0.08456 30 3.43 0.0018 Tukey-Kramer 0.1898 0.05 0.1174 0.4628 -0.05323 0.6334
hospbi*age_gr*sample C 3 1 C 6 3 0.2869 0.09062 30 3.17 0.0035 Tukey-Kramer 0.3040 0.05 0.1019 0.4720 -0.08096 0.6548
hospbi*age_gr*sample C 3 1 A 9 1 0.2144 0.1717 30 1.25 0.2213 Tukey-Kramer 0.9999 0.05 -0.1362 0.5650 -0.4826 0.9114
hospbi*age_gr*sample C 3 1 B 9 1 0.2339 0.09056 30 2.58 0.0149 Tukey-Kramer 0.6625 0.05 0.04891 0.4188 -0.1338 0.6015
hospbi*age_gr*sample C 3 1 C 9 1 0.2345 0.1003 30 2.34 0.0263 Tukey-Kramer 0.8088 0.05 0.02963 0.4393 -0.1727 0.6417
hospbi*age_gr*sample C 3 1 A 9 2 0.2905 0.3173 30 0.92 0.3671 Tukey-Kramer 1.0000 0.05 -0.3574 0.9384 -0.9975 1.5786
hospbi*age_gr*sample C 3 1 B 9 2 0.2922 0.1247 30 2.34 0.0260 Tukey-Kramer 0.8065 0.05 0.03741 0.5469 -0.2143 0.7986
hospbi*age_gr*sample C 3 1 C 9 2 0.2900 0.1516 30 1.91 0.0654 Tukey-Kramer 0.9627 0.05 -0.01967 0.5997 -0.3256 0.9056
hospbi*age_gr*sample C 3 1 A 9 3 0.2876 0.1327 30 2.17 0.0383 Tukey-Kramer 0.8883 0.05 0.01661 0.5587 -0.2511 0.8264
hospbi*age_gr*sample C 3 1 B 9 3 0.2865 0.08351 30 3.43 0.0018 Tukey-Kramer 0.1898 0.05 0.1159 0.4571 -0.05256 0.6256
hospbi*age_gr*sample C 3 1 C 9 3 0.2815 0.08890 30 3.17 0.0035 Tukey-Kramer 0.3037 0.05 0.09998 0.4631 -0.07939 0.6425
hospbi*age_gr*sample A 3 2 B 3 2 -0.00101 0.1496 30 -0.01 0.9946 Tukey-Kramer 1.0000 0.05 -0.3066 0.3046 -0.6085 0.6065
hospbi*age_gr*sample A 3 2 C 3 2 -0.00053 0.1263 30 -0.00 0.9967 Tukey-Kramer 1.0000 0.05 -0.2586 0.2575 -0.5135 0.5124
hospbi*age_gr*sample A 3 2 A 3 3 -0.00134 0.2435 30 -0.01 0.9956 Tukey-Kramer 1.0000 0.05 -0.4987 0.4960 -0.9901 0.9874
hospbi*age_gr*sample A 3 2 B 3 3 -0.00256 0.2206 30 -0.01 0.9908 Tukey-Kramer 1.0000 0.05 -0.4532 0.4480 -0.8983 0.8932
hospbi*age_gr*sample A 3 2 C 3 3 -0.00440 0.2227 30 -0.02 0.9844 Tukey-Kramer 1.0000 0.05 -0.4593 0.4505 -0.9087 0.8999
hospbi*age_gr*sample A 3 2 A 6 1 -0.01885 0.2668 30 -0.07 0.9442 Tukey-Kramer 1.0000 0.05 -0.5637 0.5260 -1.1020 1.0643
hospbi*age_gr*sample A 3 2 B 6 1 -0.01998 0.2234 30 -0.09 0.9293 Tukey-Kramer 1.0000 0.05 -0.4762 0.4363 -0.9269 0.8870
hospbi*age_gr*sample A 3 2 C 6 1 -0.01981 0.2275 30 -0.09 0.9312 Tukey-Kramer 1.0000 0.05 -0.4845 0.4448 -0.9435 0.9039
hospbi*age_gr*sample A 3 2 A 6 2 -0.02022 0.3081 30 -0.07 0.9481 Tukey-Kramer 1.0000 0.05 -0.6494 0.6089 -1.2709 1.2305
hospbi*age_gr*sample A 3 2 B 6 2 -0.01313 0.2288 30 -0.06 0.9546 Tukey-Kramer 1.0000 0.05 -0.4804 0.4542 -0.9421 0.9159
hospbi*age_gr*sample A 3 2 C 6 2 -0.04462 0.2368 30 -0.19 0.8518 Tukey-Kramer 1.0000 0.05 -0.5282 0.4390 -1.0060 0.9168
hospbi*age_gr*sample A 3 2 A 6 3 -0.00089 0.2470 30 -0.00 0.9971 Tukey-Kramer 1.0000 0.05 -0.5053 0.5036 -1.0037 1.0019
hospbi*age_gr*sample A 3 2 B 6 3 -0.00093 0.2210 30 -0.00 0.9967 Tukey-Kramer 1.0000 0.05 -0.4523 0.4505 -0.8983 0.8964
hospbi*age_gr*sample A 3 2 C 6 3 -0.00406 0.2234 30 -0.02 0.9856 Tukey-Kramer 1.0000 0.05 -0.4603 0.4522 -0.9111 0.9030
hospbi*age_gr*sample A 3 2 A 9 1 -0.07658 0.2668 30 -0.29 0.7761 Tukey-Kramer 1.0000 0.05 -0.6214 0.4683 -1.1597 1.0066
hospbi*age_gr*sample A 3 2 B 9 1 -0.05714 0.2234 30 -0.26 0.7999 Tukey-Kramer 1.0000 0.05 -0.5134 0.3991 -0.9641 0.8498
hospbi*age_gr*sample A 3 2 C 9 1 -0.05654 0.2275 30 -0.25 0.8054 Tukey-Kramer 1.0000 0.05 -0.5212 0.4081 -0.9802 0.8672
hospbi*age_gr*sample A 3 2 A 9 2 -0.00048 0.3773 30 -0.00 0.9990 Tukey-Kramer 1.0000 0.05 -0.7710 0.7701 -1.5323 1.5313
hospbi*age_gr*sample A 3 2 B 9 2 0.001161 0.2393 30 0.00 0.9962 Tukey-Kramer 1.0000 0.05 -0.4876 0.4899 -0.9704 0.9727
hospbi*age_gr*sample A 3 2 C 9 2 -0.00099 0.2544 30 -0.00 0.9969 Tukey-Kramer 1.0000 0.05 -0.5205 0.5185 -1.0337 1.0317
hospbi*age_gr*sample A 3 2 A 9 3 -0.00336 0.2435 30 -0.01 0.9891 Tukey-Kramer 1.0000 0.05 -0.5008 0.4940 -0.9922 0.9854
hospbi*age_gr*sample A 3 2 B 9 3 -0.00450 0.2206 30 -0.02 0.9839 Tukey-Kramer 1.0000 0.05 -0.4551 0.4461 -0.9003 0.8913
hospbi*age_gr*sample A 3 2 C 9 3 -0.00945 0.2227 30 -0.04 0.9664 Tukey-Kramer 1.0000 0.05 -0.4643 0.4454 -0.9137 0.8948
hospbi*age_gr*sample B 3 2 C 3 2 0.000486 0.02377 30 0.02 0.9838 Tukey-Kramer 1.0000 0.05 -0.04806 0.04903 -0.09601 0.09698
hospbi*age_gr*sample B 3 2 A 3 3 -0.00033 0.1295 30 -0.00 0.9980 Tukey-Kramer 1.0000 0.05 -0.2648 0.2641 -0.5261 0.5254
hospbi*age_gr*sample B 3 2 B 3 3 -0.00155 0.07831 30 -0.02 0.9844 Tukey-Kramer 1.0000 0.05 -0.1615 0.1584 -0.3195 0.3164
hospbi*age_gr*sample B 3 2 C 3 3 -0.00339 0.08403 30 -0.04 0.9681 Tukey-Kramer 1.0000 0.05 -0.1750 0.1682 -0.3446 0.3378
hospbi*age_gr*sample B 3 2 A 6 1 -0.01783 0.1692 30 -0.11 0.9168 Tukey-Kramer 1.0000 0.05 -0.3634 0.3277 -0.7048 0.6691
hospbi*age_gr*sample B 3 2 B 6 1 -0.01896 0.08578 30 -0.22 0.8265 Tukey-Kramer 1.0000 0.05 -0.1942 0.1562 -0.3672 0.3293
hospbi*age_gr*sample B 3 2 C 6 1 -0.01880 0.09600 30 -0.20 0.8461 Tukey-Kramer 1.0000 0.05 -0.2149 0.1773 -0.4086 0.3710
hospbi*age_gr*sample B 3 2 A 6 2 -0.01921 0.2288 30 -0.08 0.9337 Tukey-Kramer 1.0000 0.05 -0.4865 0.4481 -0.9482 0.9098
hospbi*age_gr*sample B 3 2 B 6 2 -0.01211 0.09905 30 -0.12 0.9035 Tukey-Kramer 1.0000 0.05 -0.2144 0.1902 -0.4143 0.3900
hospbi*age_gr*sample B 3 2 C 6 2 -0.04361 0.1163 30 -0.37 0.7104 Tukey-Kramer 1.0000 0.05 -0.2811 0.1939 -0.5158 0.4286
hospbi*age_gr*sample B 3 2 A 6 3 0.000120 0.1359 30 0.00 0.9993 Tukey-Kramer 1.0000 0.05 -0.2774 0.2776 -0.5515 0.5518
hospbi*age_gr*sample B 3 2 B 6 3 0.000083 0.07942 30 0.00 0.9992 Tukey-Kramer 1.0000 0.05 -0.1621 0.1623 -0.3224 0.3225
hospbi*age_gr*sample B 3 2 C 6 3 -0.00304 0.08584 30 -0.04 0.9720 Tukey-Kramer 1.0000 0.05 -0.1784 0.1723 -0.3516 0.3455
hospbi*age_gr*sample B 3 2 A 9 1 -0.07557 0.1692 30 -0.45 0.6584 Tukey-Kramer 1.0000 0.05 -0.4211 0.2700 -0.7625 0.6114
hospbi*age_gr*sample B 3 2 B 9 1 -0.05613 0.08578 30 -0.65 0.5179 Tukey-Kramer 1.0000 0.05 -0.2313 0.1191 -0.4044 0.2921
hospbi*age_gr*sample B 3 2 C 9 1 -0.05552 0.09600 30 -0.58 0.5674 Tukey-Kramer 1.0000 0.05 -0.2516 0.1405 -0.4453 0.3343
hospbi*age_gr*sample B 3 2 A 9 2 0.000530 0.3159 30 0.00 0.9987 Tukey-Kramer 1.0000 0.05 -0.6447 0.6457 -1.2821 1.2832
hospbi*age_gr*sample B 3 2 B 9 2 0.002176 0.1213 30 0.02 0.9858 Tukey-Kramer 1.0000 0.05 -0.2456 0.2499 -0.4904 0.4947
hospbi*age_gr*sample B 3 2 C 9 2 0.000027 0.1488 30 0.00 0.9999 Tukey-Kramer 1.0000 0.05 -0.3039 0.3040 -0.6042 0.6043
hospbi*age_gr*sample B 3 2 A 9 3 -0.00235 0.1295 30 -0.02 0.9856 Tukey-Kramer 1.0000 0.05 -0.2668 0.2621 -0.5281 0.5234
hospbi*age_gr*sample B 3 2 B 9 3 -0.00348 0.07831 30 -0.04 0.9648 Tukey-Kramer 1.0000 0.05 -0.1634 0.1564 -0.3214 0.3144
hospbi*age_gr*sample B 3 2 C 9 3 -0.00844 0.08403 30 -0.10 0.9207 Tukey-Kramer 1.0000 0.05 -0.1801 0.1632 -0.3496 0.3327
hospbi*age_gr*sample C 3 2 A 3 3 -0.00081 0.1431 30 -0.01 0.9955 Tukey-Kramer 1.0000 0.05 -0.2931 0.2915 -0.5819 0.5803
hospbi*age_gr*sample C 3 2 B 3 3 -0.00203 0.09924 30 -0.02 0.9838 Tukey-Kramer 1.0000 0.05 -0.2047 0.2006 -0.4049 0.4009
hospbi*age_gr*sample C 3 2 C 3 3 -0.00387 0.1038 30 -0.04 0.9705 Tukey-Kramer 1.0000 0.05 -0.2159 0.2082 -0.4254 0.4176
hospbi*age_gr*sample C 3 2 A 6 1 -0.01832 0.1799 30 -0.10 0.9196 Tukey-Kramer 1.0000 0.05 -0.3856 0.3490 -0.7485 0.7119
hospbi*age_gr*sample C 3 2 B 6 1 -0.01945 0.1052 30 -0.18 0.8546 Tukey-Kramer 1.0000 0.05 -0.2344 0.1955 -0.4467 0.4078
hospbi*age_gr*sample C 3 2 C 6 1 -0.01928 0.1137 30 -0.17 0.8665 Tukey-Kramer 1.0000 0.05 -0.2515 0.2130 -0.4810 0.4424
hospbi*age_gr*sample C 3 2 A 6 2 -0.01969 0.2368 30 -0.08 0.9343 Tukey-Kramer 1.0000 0.05 -0.5033 0.4639 -0.9811 0.9417
hospbi*age_gr*sample C 3 2 B 6 2 -0.01260 0.1163 30 -0.11 0.9145 Tukey-Kramer 1.0000 0.05 -0.2501 0.2249 -0.4848 0.4596
hospbi*age_gr*sample C 3 2 C 6 2 -0.04409 0.1313 30 -0.34 0.7394 Tukey-Kramer 1.0000 0.05 -0.3123 0.2241 -0.5772 0.4891
hospbi*age_gr*sample C 3 2 A 6 3 -0.00037 0.1489 30 -0.00 0.9981 Tukey-Kramer 1.0000 0.05 -0.3045 0.3038 -0.6050 0.6043
hospbi*age_gr*sample C 3 2 B 6 3 -0.00040 0.1001 30 -0.00 0.9968 Tukey-Kramer 1.0000 0.05 -0.2049 0.2041 -0.4069 0.4061
hospbi*age_gr*sample C 3 2 C 6 3 -0.00353 0.1053 30 -0.03 0.9735 Tukey-Kramer 1.0000 0.05 -0.2186 0.2115 -0.4310 0.4239
hospbi*age_gr*sample C 3 2 A 9 1 -0.07605 0.1799 30 -0.42 0.6754 Tukey-Kramer 1.0000 0.05 -0.4434 0.2913 -0.8063 0.6542
hospbi*age_gr*sample C 3 2 B 9 1 -0.05661 0.1052 30 -0.54 0.5946 Tukey-Kramer 1.0000 0.05 -0.2715 0.1583 -0.4839 0.3706
hospbi*age_gr*sample C 3 2 C 9 1 -0.05601 0.1137 30 -0.49 0.6260 Tukey-Kramer 1.0000 0.05 -0.2883 0.1763 -0.5177 0.4057
hospbi*age_gr*sample C 3 2 A 9 2 0.000045 0.3218 30 0.00 0.9999 Tukey-Kramer 1.0000 0.05 -0.6571 0.6572 -1.3063 1.3064
hospbi*age_gr*sample C 3 2 B 9 2 0.001691 0.1358 30 0.01 0.9901 Tukey-Kramer 1.0000 0.05 -0.2756 0.2790 -0.5495 0.5529
hospbi*age_gr*sample C 3 2 C 9 2 -0.00046 0.1608 30 -0.00 0.9977 Tukey-Kramer 1.0000 0.05 -0.3289 0.3280 -0.6534 0.6525
hospbi*age_gr*sample C 3 2 A 9 3 -0.00283 0.1431 30 -0.02 0.9843 Tukey-Kramer 1.0000 0.05 -0.2951 0.2895 -0.5839 0.5783
hospbi*age_gr*sample C 3 2 B 9 3 -0.00397 0.09924 30 -0.04 0.9684 Tukey-Kramer 1.0000 0.05 -0.2066 0.1987 -0.4069 0.3989
hospbi*age_gr*sample C 3 2 C 9 3 -0.00892 0.1038 30 -0.09 0.9321 Tukey-Kramer 1.0000 0.05 -0.2209 0.2031 -0.4304 0.4126
hospbi*age_gr*sample A 3 3 B 3 3 -0.00122 0.07481 30 -0.02 0.9871 Tukey-Kramer 1.0000 0.05 -0.1540 0.1516 -0.3050 0.3025
hospbi*age_gr*sample A 3 3 C 3 3 -0.00306 0.06317 30 -0.05 0.9617 Tukey-Kramer 1.0000 0.05 -0.1321 0.1260 -0.2595 0.2534
hospbi*age_gr*sample A 3 3 A 6 1 -0.01751 0.1887 30 -0.09 0.9267 Tukey-Kramer 1.0000 0.05 -0.4028 0.3678 -0.7834 0.7484
hospbi*age_gr*sample A 3 3 B 6 1 -0.01864 0.1196 30 -0.16 0.8773 Tukey-Kramer 1.0000 0.05 -0.2630 0.2257 -0.5044 0.4671
hospbi*age_gr*sample A 3 3 C 6 1 -0.01847 0.1272 30 -0.15 0.8855 Tukey-Kramer 1.0000 0.05 -0.2782 0.2413 -0.5348 0.4979
hospbi*age_gr*sample A 3 3 A 6 2 -0.01888 0.2435 30 -0.08 0.9387 Tukey-Kramer 1.0000 0.05 -0.5163 0.4785 -1.0077 0.9699
hospbi*age_gr*sample A 3 3 B 6 2 -0.01178 0.1295 30 -0.09 0.9281 Tukey-Kramer 1.0000 0.05 -0.2762 0.2527 -0.5375 0.5140
hospbi*age_gr*sample A 3 3 C 6 2 -0.04328 0.1431 30 -0.30 0.7644 Tukey-Kramer 1.0000 0.05 -0.3356 0.2490 -0.6244 0.5378
hospbi*age_gr*sample A 3 3 A 6 3 0.000447 0.1594 30 0.00 0.9978 Tukey-Kramer 1.0000 0.05 -0.3252 0.3261 -0.6469 0.6478
hospbi*age_gr*sample A 3 3 B 6 3 0.000410 0.1152 30 0.00 0.9972 Tukey-Kramer 1.0000 0.05 -0.2348 0.2356 -0.4672 0.4680
hospbi*age_gr*sample A 3 3 C 6 3 -0.00272 0.1197 30 -0.02 0.9821 Tukey-Kramer 1.0000 0.05 -0.2472 0.2417 -0.4887 0.4832
hospbi*age_gr*sample A 3 3 A 9 1 -0.07524 0.1887 30 -0.40 0.6928 Tukey-Kramer 1.0000 0.05 -0.4605 0.3100 -0.8412 0.6907
hospbi*age_gr*sample A 3 3 B 9 1 -0.05580 0.1196 30 -0.47 0.6443 Tukey-Kramer 1.0000 0.05 -0.3002 0.1886 -0.5416 0.4300
hospbi*age_gr*sample A 3 3 C 9 1 -0.05519 0.1272 30 -0.43 0.6674 Tukey-Kramer 1.0000 0.05 -0.3149 0.2045 -0.5715 0.4611
hospbi*age_gr*sample A 3 3 A 9 2 0.000857 0.3268 30 0.00 0.9979 Tukey-Kramer 1.0000 0.05 -0.6665 0.6682 -1.3257 1.3275
hospbi*age_gr*sample A 3 3 B 9 2 0.002503 0.1472 30 0.02 0.9865 Tukey-Kramer 1.0000 0.05 -0.2982 0.3032 -0.5952 0.6002
hospbi*age_gr*sample A 3 3 C 9 2 0.000354 0.1706 30 0.00 0.9984 Tukey-Kramer 1.0000 0.05 -0.3481 0.3488 -0.6923 0.6930
hospbi*age_gr*sample A 3 3 A 9 3 -0.00202 0.1540 30 -0.01 0.9896 Tukey-Kramer 1.0000 0.05 -0.3166 0.3126 -0.6274 0.6233
hospbi*age_gr*sample A 3 3 B 9 3 -0.00316 0.1144 30 -0.03 0.9782 Tukey-Kramer 1.0000 0.05 -0.2368 0.2305 -0.4677 0.4613
hospbi*age_gr*sample A 3 3 C 9 3 -0.00811 0.1184 30 -0.07 0.9459 Tukey-Kramer 1.0000 0.05 -0.2499 0.2337 -0.4888 0.4726
hospbi*age_gr*sample B 3 3 C 3 3 -0.00184 0.01188 30 -0.15 0.8782 Tukey-Kramer 1.0000 0.05 -0.02611 0.02243 -0.05009 0.04641
hospbi*age_gr*sample B 3 3 A 6 1 -0.01628 0.1580 30 -0.10 0.9186 Tukey-Kramer 1.0000 0.05 -0.3389 0.3063 -0.6576 0.6250
hospbi*age_gr*sample B 3 3 B 6 1 -0.01742 0.06066 30 -0.29 0.7760 Tukey-Kramer 1.0000 0.05 -0.1413 0.1065 -0.2637 0.2288
hospbi*age_gr*sample B 3 3 C 6 1 -0.01725 0.07441 30 -0.23 0.8183 Tukey-Kramer 1.0000 0.05 -0.1692 0.1347 -0.3194 0.2849
hospbi*age_gr*sample B 3 3 A 6 2 -0.01766 0.2206 30 -0.08 0.9367 Tukey-Kramer 1.0000 0.05 -0.4682 0.4329 -0.9134 0.8781
hospbi*age_gr*sample B 3 3 B 6 2 -0.01056 0.07831 30 -0.13 0.8936 Tukey-Kramer 1.0000 0.05 -0.1705 0.1494 -0.3285 0.3074
hospbi*age_gr*sample B 3 3 C 6 2 -0.04206 0.09924 30 -0.42 0.6747 Tukey-Kramer 1.0000 0.05 -0.2447 0.1606 -0.4450 0.3609
hospbi*age_gr*sample B 3 3 A 6 3 0.001668 0.1216 30 0.01 0.9891 Tukey-Kramer 1.0000 0.05 -0.2467 0.2500 -0.4920 0.4953
hospbi*age_gr*sample B 3 3 B 6 3 0.001631 0.05126 30 0.03 0.9748 Tukey-Kramer 1.0000 0.05 -0.1031 0.1063 -0.2065 0.2098
hospbi*age_gr*sample B 3 3 C 6 3 -0.00149 0.06074 30 -0.02 0.9805 Tukey-Kramer 1.0000 0.05 -0.1256 0.1226 -0.2481 0.2451
hospbi*age_gr*sample B 3 3 A 9 1 -0.07402 0.1580 30 -0.47 0.6428 Tukey-Kramer 1.0000 0.05 -0.3966 0.2486 -0.7153 0.5673
hospbi*age_gr*sample B 3 3 B 9 1 -0.05458 0.06066 30 -0.90 0.3754 Tukey-Kramer 1.0000 0.05 -0.1785 0.06930 -0.3008 0.1917
hospbi*age_gr*sample B 3 3 C 9 1 -0.05397 0.07441 30 -0.73 0.4739 Tukey-Kramer 1.0000 0.05 -0.2059 0.09800 -0.3561 0.2481
hospbi*age_gr*sample B 3 3 A 9 2 0.002078 0.3100 30 0.01 0.9947 Tukey-Kramer 1.0000 0.05 -0.6311 0.6353 -1.2567 1.2609
hospbi*age_gr*sample B 3 3 B 9 2 0.003724 0.1051 30 0.04 0.9720 Tukey-Kramer 1.0000 0.05 -0.2108 0.2183 -0.4228 0.4303
hospbi*age_gr*sample B 3 3 C 9 2 0.001575 0.1359 30 0.01 0.9908 Tukey-Kramer 1.0000 0.05 -0.2760 0.2791 -0.5502 0.5534
hospbi*age_gr*sample B 3 3 A 9 3 -0.00080 0.1144 30 -0.01 0.9945 Tukey-Kramer 1.0000 0.05 -0.2345 0.2329 -0.4653 0.4637
hospbi*age_gr*sample B 3 3 B 9 3 -0.00194 0.04953 30 -0.04 0.9691 Tukey-Kramer 1.0000 0.05 -0.1031 0.09921 -0.2030 0.1991
hospbi*age_gr*sample B 3 3 C 9 3 -0.00689 0.05816 30 -0.12 0.9065 Tukey-Kramer 1.0000 0.05 -0.1257 0.1119 -0.2430 0.2292
hospbi*age_gr*sample C 3 3 A 6 1 -0.01445 0.1609 30 -0.09 0.9290 Tukey-Kramer 1.0000 0.05 -0.3430 0.3141 -0.6676 0.6387
hospbi*age_gr*sample C 3 3 B 6 1 -0.01558 0.06789 30 -0.23 0.8200 Tukey-Kramer 1.0000 0.05 -0.1542 0.1231 -0.2912 0.2600
hospbi*age_gr*sample C 3 3 C 6 1 -0.01541 0.08042 30 -0.19 0.8493 Tukey-Kramer 1.0000 0.05 -0.1796 0.1488 -0.3419 0.3111
hospbi*age_gr*sample C 3 3 A 6 2 -0.01582 0.2227 30 -0.07 0.9438 Tukey-Kramer 1.0000 0.05 -0.4707 0.4390 -0.9201 0.8884
hospbi*age_gr*sample C 3 3 B 6 2 -0.00873 0.08403 30 -0.10 0.9180 Tukey-Kramer 1.0000 0.05 -0.1803 0.1629 -0.3499 0.3324
hospbi*age_gr*sample C 3 3 C 6 2 -0.04022 0.1038 30 -0.39 0.7012 Tukey-Kramer 1.0000 0.05 -0.2522 0.1718 -0.4617 0.3813
hospbi*age_gr*sample C 3 3 A 6 3 0.003505 0.1254 30 0.03 0.9779 Tukey-Kramer 1.0000 0.05 -0.2525 0.2595 -0.5054 0.5124
hospbi*age_gr*sample C 3 3 B 6 3 0.003468 0.05964 30 0.06 0.9540 Tukey-Kramer 1.0000 0.05 -0.1183 0.1253 -0.2387 0.2456
hospbi*age_gr*sample C 3 3 C 6 3 0.000343 0.06796 30 0.01 0.9960 Tukey-Kramer 1.0000 0.05 -0.1385 0.1391 -0.2756 0.2763
hospbi*age_gr*sample C 3 3 A 9 1 -0.07218 0.1609 30 -0.45 0.6569 Tukey-Kramer 1.0000 0.05 -0.4007 0.2564 -0.7253 0.5810
hospbi*age_gr*sample C 3 3 B 9 1 -0.05274 0.06789 30 -0.78 0.4433 Tukey-Kramer 1.0000 0.05 -0.1914 0.08590 -0.3284 0.2229
hospbi*age_gr*sample C 3 3 C 9 1 -0.05214 0.08042 30 -0.65 0.5217 Tukey-Kramer 1.0000 0.05 -0.2164 0.1121 -0.3786 0.2743
hospbi*age_gr*sample C 3 3 A 9 2 0.003915 0.3115 30 0.01 0.9901 Tukey-Kramer 1.0000 0.05 -0.6323 0.6402 -1.2609 1.2688
hospbi*age_gr*sample C 3 3 B 9 2 0.005561 0.1094 30 0.05 0.9598 Tukey-Kramer 1.0000 0.05 -0.2179 0.2290 -0.4386 0.4497
hospbi*age_gr*sample C 3 3 C 9 2 0.003412 0.1393 30 0.02 0.9806 Tukey-Kramer 1.0000 0.05 -0.2810 0.2879 -0.5621 0.5689
hospbi*age_gr*sample C 3 3 A 9 3 0.001036 0.1184 30 0.01 0.9931 Tukey-Kramer 1.0000 0.05 -0.2408 0.2428 -0.4797 0.4817
hospbi*age_gr*sample C 3 3 B 9 3 -0.00010 0.05816 30 -0.00 0.9987 Tukey-Kramer 1.0000 0.05 -0.1189 0.1187 -0.2362 0.2360
hospbi*age_gr*sample C 3 3 C 9 3 -0.00505 0.06566 30 -0.08 0.9392 Tukey-Kramer 1.0000 0.05 -0.1391 0.1290 -0.2716 0.2615
hospbi*age_gr*sample A 6 1 B 6 1 -0.00113 0.1058 30 -0.01 0.9915 Tukey-Kramer 1.0000 0.05 -0.2172 0.2149 -0.4307 0.4284
hospbi*age_gr*sample A 6 1 C 6 1 -0.00097 0.08934 30 -0.01 0.9914 Tukey-Kramer 1.0000 0.05 -0.1834 0.1815 -0.3637 0.3618
hospbi*age_gr*sample A 6 1 A 6 2 -0.00137 0.2668 30 -0.01 0.9959 Tukey-Kramer 1.0000 0.05 -0.5462 0.5435 -1.0845 1.0818
hospbi*age_gr*sample A 6 1 B 6 2 0.005721 0.1692 30 0.03 0.9733 Tukey-Kramer 1.0000 0.05 -0.3399 0.3513 -0.6813 0.6927
hospbi*age_gr*sample A 6 1 C 6 2 -0.02577 0.1799 30 -0.14 0.8870 Tukey-Kramer 1.0000 0.05 -0.3931 0.3415 -0.7560 0.7044
hospbi*age_gr*sample A 6 1 A 6 3 0.01795 0.1931 30 0.09 0.9265 Tukey-Kramer 1.0000 0.05 -0.3764 0.4123 -0.7660 0.8019
hospbi*age_gr*sample A 6 1 B 6 3 0.01792 0.1585 30 0.11 0.9108 Tukey-Kramer 1.0000 0.05 -0.3058 0.3417 -0.6257 0.6615
hospbi*age_gr*sample A 6 1 C 6 3 0.01479 0.1618 30 0.09 0.9278 Tukey-Kramer 1.0000 0.05 -0.3157 0.3453 -0.6422 0.6718
hospbi*age_gr*sample A 6 1 A 9 1 -0.05773 0.2178 30 -0.27 0.7928 Tukey-Kramer 1.0000 0.05 -0.5026 0.3871 -0.9421 0.8267
hospbi*age_gr*sample A 6 1 B 9 1 -0.03830 0.1618 30 -0.24 0.8145 Tukey-Kramer 1.0000 0.05 -0.3687 0.2921 -0.6952 0.6186
hospbi*age_gr*sample A 6 1 C 9 1 -0.03769 0.1674 30 -0.23 0.8234 Tukey-Kramer 1.0000 0.05 -0.3797 0.3043 -0.7175 0.6421
hospbi*age_gr*sample A 6 1 A 9 2 0.01836 0.3444 30 0.05 0.9578 Tukey-Kramer 1.0000 0.05 -0.6851 0.7218 -1.3800 1.4167
hospbi*age_gr*sample A 6 1 B 9 2 0.02001 0.1831 30 0.11 0.9137 Tukey-Kramer 1.0000 0.05 -0.3540 0.3940 -0.7235 0.7635
hospbi*age_gr*sample A 6 1 C 9 2 0.01786 0.2024 30 0.09 0.9303 Tukey-Kramer 1.0000 0.05 -0.3955 0.4312 -0.8039 0.8396
hospbi*age_gr*sample A 6 1 A 9 3 0.01548 0.1887 30 0.08 0.9351 Tukey-Kramer 1.0000 0.05 -0.3698 0.4008 -0.7504 0.7814
hospbi*age_gr*sample A 6 1 B 9 3 0.01435 0.1580 30 0.09 0.9282 Tukey-Kramer 1.0000 0.05 -0.3083 0.3370 -0.6270 0.6557
hospbi*age_gr*sample A 6 1 C 9 3 0.009397 0.1609 30 0.06 0.9538 Tukey-Kramer 1.0000 0.05 -0.3192 0.3380 -0.6438 0.6626
hospbi*age_gr*sample B 6 1 C 6 1 0.000166 0.01681 30 0.01 0.9922 Tukey-Kramer 1.0000 0.05 -0.03416 0.03449 -0.06807 0.06840
hospbi*age_gr*sample B 6 1 A 6 2 -0.00024 0.2234 30 -0.00 0.9991 Tukey-Kramer 1.0000 0.05 -0.4565 0.4560 -0.9072 0.9067
hospbi*age_gr*sample B 6 1 B 6 2 0.006853 0.08578 30 0.08 0.9369 Tukey-Kramer 1.0000 0.05 -0.1683 0.1820 -0.3414 0.3551
hospbi*age_gr*sample B 6 1 C 6 2 -0.02464 0.1052 30 -0.23 0.8165 Tukey-Kramer 1.0000 0.05 -0.2396 0.1903 -0.4519 0.4026
hospbi*age_gr*sample B 6 1 A 6 3 0.01908 0.1265 30 0.15 0.8811 Tukey-Kramer 1.0000 0.05 -0.2393 0.2775 -0.4946 0.5328
hospbi*age_gr*sample B 6 1 B 6 3 0.01905 0.06208 30 0.31 0.7611 Tukey-Kramer 1.0000 0.05 -0.1077 0.1458 -0.2330 0.2711
hospbi*age_gr*sample B 6 1 C 6 3 0.01592 0.07012 30 0.23 0.8219 Tukey-Kramer 1.0000 0.05 -0.1273 0.1591 -0.2687 0.3006
hospbi*age_gr*sample B 6 1 A 9 1 -0.05660 0.1618 30 -0.35 0.7289 Tukey-Kramer 1.0000 0.05 -0.3870 0.2738 -0.7135 0.6003
hospbi*age_gr*sample B 6 1 B 9 1 -0.03716 0.07004 30 -0.53 0.5996 Tukey-Kramer 1.0000 0.05 -0.1802 0.1059 -0.3215 0.2472
hospbi*age_gr*sample B 6 1 C 9 1 -0.03656 0.08224 30 -0.44 0.6599 Tukey-Kramer 1.0000 0.05 -0.2045 0.1314 -0.3705 0.2973
hospbi*age_gr*sample B 6 1 A 9 2 0.01949 0.3120 30 0.06 0.9506 Tukey-Kramer 1.0000 0.05 -0.6177 0.6567 -1.2473 1.2863
hospbi*age_gr*sample B 6 1 B 9 2 0.02114 0.1107 30 0.19 0.8499 Tukey-Kramer 1.0000 0.05 -0.2050 0.2473 -0.4285 0.4708
hospbi*age_gr*sample B 6 1 C 9 2 0.01899 0.1403 30 0.14 0.8933 Tukey-Kramer 1.0000 0.05 -0.2676 0.3056 -0.5508 0.5888
hospbi*age_gr*sample B 6 1 A 9 3 0.01661 0.1196 30 0.14 0.8905 Tukey-Kramer 1.0000 0.05 -0.2277 0.2610 -0.4692 0.5024
hospbi*age_gr*sample B 6 1 B 9 3 0.01548 0.06066 30 0.26 0.8003 Tukey-Kramer 1.0000 0.05 -0.1084 0.1394 -0.2308 0.2617
hospbi*age_gr*sample B 6 1 C 9 3 0.01053 0.06789 30 0.16 0.8778 Tukey-Kramer 1.0000 0.05 -0.1281 0.1492 -0.2651 0.2861
hospbi*age_gr*sample C 6 1 A 6 2 -0.00041 0.2275 30 -0.00 0.9986 Tukey-Kramer 1.0000 0.05 -0.4651 0.4642 -0.9241 0.9233
hospbi*age_gr*sample C 6 1 B 6 2 0.006687 0.09600 30 0.07 0.9449 Tukey-Kramer 1.0000 0.05 -0.1894 0.2028 -0.3831 0.3965
hospbi*age_gr*sample C 6 1 C 6 2 -0.02481 0.1137 30 -0.22 0.8288 Tukey-Kramer 1.0000 0.05 -0.2571 0.2074 -0.4865 0.4369
hospbi*age_gr*sample C 6 1 A 6 3 0.01892 0.1337 30 0.14 0.8884 Tukey-Kramer 1.0000 0.05 -0.2541 0.2919 -0.5238 0.5616
hospbi*age_gr*sample C 6 1 B 6 3 0.01888 0.07558 30 0.25 0.8044 Tukey-Kramer 1.0000 0.05 -0.1355 0.1732 -0.2880 0.3257
hospbi*age_gr*sample C 6 1 C 6 3 0.01576 0.08231 30 0.19 0.8495 Tukey-Kramer 1.0000 0.05 -0.1523 0.1839 -0.3184 0.3499
hospbi*age_gr*sample C 6 1 A 9 1 -0.05677 0.1674 30 -0.34 0.7370 Tukey-Kramer 1.0000 0.05 -0.3987 0.2852 -0.7366 0.6230
hospbi*age_gr*sample C 6 1 B 9 1 -0.03733 0.08224 30 -0.45 0.6532 Tukey-Kramer 1.0000 0.05 -0.2053 0.1306 -0.3712 0.2966
hospbi*age_gr*sample C 6 1 C 9 1 -0.03672 0.09286 30 -0.40 0.6953 Tukey-Kramer 1.0000 0.05 -0.2264 0.1529 -0.4137 0.3403
hospbi*age_gr*sample C 6 1 A 9 2 0.01933 0.3150 30 0.06 0.9515 Tukey-Kramer 1.0000 0.05 -0.6240 0.6626 -1.2595 1.2982
hospbi*age_gr*sample C 6 1 B 9 2 0.02097 0.1188 30 0.18 0.8611 Tukey-Kramer 1.0000 0.05 -0.2217 0.2637 -0.4615 0.5035
hospbi*age_gr*sample C 6 1 C 9 2 0.01883 0.1468 30 0.13 0.8988 Tukey-Kramer 1.0000 0.05 -0.2810 0.3187 -0.5772 0.6149
hospbi*age_gr*sample C 6 1 A 9 3 0.01645 0.1272 30 0.13 0.8980 Tukey-Kramer 1.0000 0.05 -0.2433 0.2762 -0.4999 0.5328
hospbi*age_gr*sample C 6 1 B 9 3 0.01531 0.07441 30 0.21 0.8383 Tukey-Kramer 1.0000 0.05 -0.1367 0.1673 -0.2868 0.3174
hospbi*age_gr*sample C 6 1 C 9 3 0.01036 0.08042 30 0.13 0.8983 Tukey-Kramer 1.0000 0.05 -0.1539 0.1746 -0.3161 0.3368
hospbi*age_gr*sample A 6 2 B 6 2 0.007095 0.1496 30 0.05 0.9625 Tukey-Kramer 1.0000 0.05 -0.2985 0.3127 -0.6004 0.6146
hospbi*age_gr*sample A 6 2 C 6 2 -0.02440 0.1263 30 -0.19 0.8482 Tukey-Kramer 1.0000 0.05 -0.2824 0.2336 -0.5374 0.4886
hospbi*age_gr*sample A 6 2 A 6 3 0.01933 0.2470 30 0.08 0.9382 Tukey-Kramer 1.0000 0.05 -0.4851 0.5238 -0.9835 1.0221
hospbi*age_gr*sample A 6 2 B 6 3 0.01929 0.2210 30 0.09 0.9310 Tukey-Kramer 1.0000 0.05 -0.4321 0.4707 -0.8781 0.9167
hospbi*age_gr*sample A 6 2 C 6 3 0.01616 0.2234 30 0.07 0.9428 Tukey-Kramer 1.0000 0.05 -0.4401 0.4724 -0.8909 0.9232
hospbi*age_gr*sample A 6 2 A 9 1 -0.05636 0.2668 30 -0.21 0.8341 Tukey-Kramer 1.0000 0.05 -0.6012 0.4885 -1.1395 1.0268
hospbi*age_gr*sample A 6 2 B 9 1 -0.03692 0.2234 30 -0.17 0.8698 Tukey-Kramer 1.0000 0.05 -0.4932 0.4193 -0.9439 0.8700
hospbi*age_gr*sample A 6 2 C 9 1 -0.03631 0.2275 30 -0.16 0.8743 Tukey-Kramer 1.0000 0.05 -0.5010 0.4283 -0.9600 0.8874
hospbi*age_gr*sample A 6 2 A 9 2 0.01974 0.3773 30 0.05 0.9586 Tukey-Kramer 1.0000 0.05 -0.7508 0.7903 -1.5121 1.5516
hospbi*age_gr*sample A 6 2 B 9 2 0.02138 0.2393 30 0.09 0.9294 Tukey-Kramer 1.0000 0.05 -0.4673 0.5101 -0.9502 0.9929
hospbi*age_gr*sample A 6 2 C 9 2 0.01923 0.2544 30 0.08 0.9402 Tukey-Kramer 1.0000 0.05 -0.5002 0.5387 -1.0134 1.0519
hospbi*age_gr*sample A 6 2 A 9 3 0.01686 0.2435 30 0.07 0.9453 Tukey-Kramer 1.0000 0.05 -0.4805 0.5142 -0.9719 1.0056
hospbi*age_gr*sample A 6 2 B 9 3 0.01572 0.2206 30 0.07 0.9437 Tukey-Kramer 1.0000 0.05 -0.4349 0.4663 -0.8800 0.9115
hospbi*age_gr*sample A 6 2 C 9 3 0.01077 0.2227 30 0.05 0.9618 Tukey-Kramer 1.0000 0.05 -0.4441 0.4656 -0.8935 0.9150
hospbi*age_gr*sample B 6 2 C 6 2 -0.03150 0.02377 30 -1.33 0.1951 Tukey-Kramer 0.9997 0.05 -0.08004 0.01705 -0.1280 0.06500
hospbi*age_gr*sample B 6 2 A 6 3 0.01223 0.1359 30 0.09 0.9289 Tukey-Kramer 1.0000 0.05 -0.2653 0.2897 -0.5394 0.5639
hospbi*age_gr*sample B 6 2 B 6 3 0.01219 0.07942 30 0.15 0.8790 Tukey-Kramer 1.0000 0.05 -0.1500 0.1744 -0.3102 0.3346
hospbi*age_gr*sample B 6 2 C 6 3 0.009069 0.08584 30 0.11 0.9166 Tukey-Kramer 1.0000 0.05 -0.1662 0.1844 -0.3395 0.3576
hospbi*age_gr*sample B 6 2 A 9 1 -0.06345 0.1692 30 -0.38 0.7103 Tukey-Kramer 1.0000 0.05 -0.4090 0.2821 -0.7504 0.6235
hospbi*age_gr*sample B 6 2 B 9 1 -0.04402 0.08578 30 -0.51 0.6116 Tukey-Kramer 1.0000 0.05 -0.2192 0.1312 -0.3923 0.3043
hospbi*age_gr*sample B 6 2 C 9 1 -0.04341 0.09600 30 -0.45 0.6544 Tukey-Kramer 1.0000 0.05 -0.2395 0.1527 -0.4332 0.3464
hospbi*age_gr*sample B 6 2 A 9 2 0.01264 0.3159 30 0.04 0.9683 Tukey-Kramer 1.0000 0.05 -0.6326 0.6579 -1.2700 1.2953
hospbi*age_gr*sample B 6 2 B 9 2 0.01429 0.1213 30 0.12 0.9070 Tukey-Kramer 1.0000 0.05 -0.2335 0.2620 -0.4782 0.5068
hospbi*age_gr*sample B 6 2 C 9 2 0.01214 0.1488 30 0.08 0.9355 Tukey-Kramer 1.0000 0.05 -0.2918 0.3161 -0.5921 0.6164
hospbi*age_gr*sample B 6 2 A 9 3 0.009762 0.1295 30 0.08 0.9404 Tukey-Kramer 1.0000 0.05 -0.2547 0.2742 -0.5160 0.5355
hospbi*age_gr*sample B 6 2 B 9 3 0.008627 0.07831 30 0.11 0.9130 Tukey-Kramer 1.0000 0.05 -0.1513 0.1686 -0.3093 0.3266
hospbi*age_gr*sample B 6 2 C 9 3 0.003676 0.08403 30 0.04 0.9654 Tukey-Kramer 1.0000 0.05 -0.1679 0.1753 -0.3375 0.3448
hospbi*age_gr*sample C 6 2 A 6 3 0.04373 0.1489 30 0.29 0.7711 Tukey-Kramer 1.0000 0.05 -0.2604 0.3479 -0.5609 0.6484
hospbi*age_gr*sample C 6 2 B 6 3 0.04369 0.1001 30 0.44 0.6657 Tukey-Kramer 1.0000 0.05 -0.1608 0.2482 -0.3628 0.4502
hospbi*age_gr*sample C 6 2 C 6 3 0.04056 0.1053 30 0.39 0.7028 Tukey-Kramer 1.0000 0.05 -0.1745 0.2556 -0.3869 0.4680
hospbi*age_gr*sample C 6 2 A 9 1 -0.03196 0.1799 30 -0.18 0.8602 Tukey-Kramer 1.0000 0.05 -0.3993 0.3354 -0.7622 0.6982
hospbi*age_gr*sample C 6 2 B 9 1 -0.01252 0.1052 30 -0.12 0.9061 Tukey-Kramer 1.0000 0.05 -0.2274 0.2024 -0.4398 0.4147
hospbi*age_gr*sample C 6 2 C 9 1 -0.01191 0.1137 30 -0.10 0.9173 Tukey-Kramer 1.0000 0.05 -0.2442 0.2203 -0.4736 0.4498
hospbi*age_gr*sample C 6 2 A 9 2 0.04414 0.3218 30 0.14 0.8918 Tukey-Kramer 1.0000 0.05 -0.6130 0.7012 -1.2622 1.3504
hospbi*age_gr*sample C 6 2 B 9 2 0.04578 0.1358 30 0.34 0.7383 Tukey-Kramer 1.0000 0.05 -0.2315 0.3231 -0.5054 0.5970
hospbi*age_gr*sample C 6 2 C 9 2 0.04363 0.1608 30 0.27 0.7880 Tukey-Kramer 1.0000 0.05 -0.2848 0.3721 -0.6093 0.6966
hospbi*age_gr*sample C 6 2 A 9 3 0.04126 0.1431 30 0.29 0.7751 Tukey-Kramer 1.0000 0.05 -0.2510 0.3336 -0.5398 0.6223
hospbi*age_gr*sample C 6 2 B 9 3 0.04012 0.09924 30 0.40 0.6889 Tukey-Kramer 1.0000 0.05 -0.1626 0.2428 -0.3628 0.4430
hospbi*age_gr*sample C 6 2 C 9 3 0.03517 0.1038 30 0.34 0.7371 Tukey-Kramer 1.0000 0.05 -0.1769 0.2472 -0.3863 0.4567
hospbi*age_gr*sample A 6 3 B 6 3 -0.00004 0.07998 30 -0.00 0.9996 Tukey-Kramer 1.0000 0.05 -0.1634 0.1633 -0.3247 0.3247
hospbi*age_gr*sample A 6 3 C 6 3 -0.00316 0.06753 30 -0.05 0.9630 Tukey-Kramer 1.0000 0.05 -0.1411 0.1348 -0.2774 0.2710
hospbi*age_gr*sample A 6 3 A 9 1 -0.07569 0.1931 30 -0.39 0.6978 Tukey-Kramer 1.0000 0.05 -0.4700 0.3187 -0.8596 0.7082
hospbi*age_gr*sample A 6 3 B 9 1 -0.05625 0.1265 30 -0.44 0.6598 Tukey-Kramer 1.0000 0.05 -0.3147 0.2022 -0.5700 0.4575
hospbi*age_gr*sample A 6 3 C 9 1 -0.05564 0.1337 30 -0.42 0.6802 Tukey-Kramer 1.0000 0.05 -0.3286 0.2174 -0.5984 0.4871
hospbi*age_gr*sample A 6 3 A 9 2 0.000410 0.3293 30 0.00 0.9990 Tukey-Kramer 1.0000 0.05 -0.6722 0.6730 -1.3367 1.3375
hospbi*age_gr*sample A 6 3 B 9 2 0.002056 0.1529 30 0.01 0.9894 Tukey-Kramer 1.0000 0.05 -0.3101 0.3143 -0.6186 0.6227
hospbi*age_gr*sample A 6 3 C 9 2 -0.00009 0.1755 30 -0.00 0.9996 Tukey-Kramer 1.0000 0.05 -0.3585 0.3583 -0.7126 0.7125
hospbi*age_gr*sample A 6 3 A 9 3 -0.00247 0.1594 30 -0.02 0.9877 Tukey-Kramer 1.0000 0.05 -0.3281 0.3231 -0.6498 0.6448
hospbi*age_gr*sample A 6 3 B 9 3 -0.00360 0.1216 30 -0.03 0.9765 Tukey-Kramer 1.0000 0.05 -0.2519 0.2447 -0.4973 0.4900
hospbi*age_gr*sample A 6 3 C 9 3 -0.00856 0.1254 30 -0.07 0.9460 Tukey-Kramer 1.0000 0.05 -0.2646 0.2474 -0.5175 0.5004
hospbi*age_gr*sample B 6 3 C 6 3 -0.00313 0.01270 30 -0.25 0.8074 Tukey-Kramer 1.0000 0.05 -0.02907 0.02282 -0.05470 0.04845
hospbi*age_gr*sample B 6 3 A 9 1 -0.07565 0.1585 30 -0.48 0.6367 Tukey-Kramer 1.0000 0.05 -0.3994 0.2481 -0.7192 0.5679
hospbi*age_gr*sample B 6 3 B 9 1 -0.05621 0.06208 30 -0.91 0.3725 Tukey-Kramer 1.0000 0.05 -0.1830 0.07058 -0.3083 0.1958
hospbi*age_gr*sample B 6 3 C 9 1 -0.05560 0.07558 30 -0.74 0.4676 Tukey-Kramer 1.0000 0.05 -0.2100 0.09876 -0.3625 0.2513
hospbi*age_gr*sample B 6 3 A 9 2 0.000447 0.3103 30 0.00 0.9989 Tukey-Kramer 1.0000 0.05 -0.6333 0.6342 -1.2595 1.2604
hospbi*age_gr*sample B 6 3 B 9 2 0.002093 0.1059 30 0.02 0.9844 Tukey-Kramer 1.0000 0.05 -0.2142 0.2184 -0.4278 0.4320
hospbi*age_gr*sample B 6 3 C 9 2 -0.00006 0.1366 30 -0.00 0.9997 Tukey-Kramer 1.0000 0.05 -0.2789 0.2788 -0.5544 0.5543
hospbi*age_gr*sample B 6 3 A 9 3 -0.00243 0.1152 30 -0.02 0.9833 Tukey-Kramer 1.0000 0.05 -0.2376 0.2328 -0.4700 0.4652
hospbi*age_gr*sample B 6 3 B 9 3 -0.00357 0.05126 30 -0.07 0.9450 Tukey-Kramer 1.0000 0.05 -0.1083 0.1011 -0.2117 0.2046
hospbi*age_gr*sample B 6 3 C 9 3 -0.00852 0.05964 30 -0.14 0.8874 Tukey-Kramer 1.0000 0.05 -0.1303 0.1133 -0.2507 0.2336
hospbi*age_gr*sample C 6 3 A 9 1 -0.07252 0.1618 30 -0.45 0.6573 Tukey-Kramer 1.0000 0.05 -0.4030 0.2580 -0.7296 0.5845
hospbi*age_gr*sample C 6 3 B 9 1 -0.05309 0.07012 30 -0.76 0.4549 Tukey-Kramer 1.0000 0.05 -0.1963 0.09011 -0.3378 0.2316
hospbi*age_gr*sample C 6 3 C 9 1 -0.05248 0.08231 30 -0.64 0.5286 Tukey-Kramer 1.0000 0.05 -0.2206 0.1156 -0.3866 0.2817
hospbi*age_gr*sample C 6 3 A 9 2 0.003572 0.3120 30 0.01 0.9909 Tukey-Kramer 1.0000 0.05 -0.6337 0.6408 -1.2633 1.2704
hospbi*age_gr*sample C 6 3 B 9 2 0.005218 0.1108 30 0.05 0.9627 Tukey-Kramer 1.0000 0.05 -0.2211 0.2315 -0.4446 0.4550
hospbi*age_gr*sample C 6 3 C 9 2 0.003069 0.1404 30 0.02 0.9827 Tukey-Kramer 1.0000 0.05 -0.2836 0.2898 -0.5669 0.5730
hospbi*age_gr*sample C 6 3 A 9 3 0.000693 0.1197 30 0.01 0.9954 Tukey-Kramer 1.0000 0.05 -0.2438 0.2451 -0.4853 0.4866
hospbi*age_gr*sample C 6 3 B 9 3 -0.00044 0.06074 30 -0.01 0.9942 Tukey-Kramer 1.0000 0.05 -0.1245 0.1236 -0.2471 0.2462
hospbi*age_gr*sample C 6 3 C 9 3 -0.00539 0.06796 30 -0.08 0.9373 Tukey-Kramer 1.0000 0.05 -0.1442 0.1334 -0.2813 0.2705
hospbi*age_gr*sample A 9 1 B 9 1 0.01944 0.1058 30 0.18 0.8555 Tukey-Kramer 1.0000 0.05 -0.1966 0.2355 -0.4101 0.4490
hospbi*age_gr*sample A 9 1 C 9 1 0.02004 0.08934 30 0.22 0.8240 Tukey-Kramer 1.0000 0.05 -0.1624 0.2025 -0.3427 0.3828
hospbi*age_gr*sample A 9 1 A 9 2 0.07610 0.3444 30 0.22 0.8266 Tukey-Kramer 1.0000 0.05 -0.6273 0.7795 -1.3223 1.4745
hospbi*age_gr*sample A 9 1 B 9 2 0.07774 0.1831 30 0.42 0.6742 Tukey-Kramer 1.0000 0.05 -0.2963 0.4517 -0.6658 0.8213
hospbi*age_gr*sample A 9 1 C 9 2 0.07559 0.2024 30 0.37 0.7114 Tukey-Kramer 1.0000 0.05 -0.3378 0.4890 -0.7462 0.8974
hospbi*age_gr*sample A 9 1 A 9 3 0.07322 0.1887 30 0.39 0.7007 Tukey-Kramer 1.0000 0.05 -0.3121 0.4585 -0.6927 0.8391
hospbi*age_gr*sample A 9 1 B 9 3 0.07208 0.1580 30 0.46 0.6514 Tukey-Kramer 1.0000 0.05 -0.2505 0.3947 -0.5692 0.7134
hospbi*age_gr*sample A 9 1 C 9 3 0.06713 0.1609 30 0.42 0.6794 Tukey-Kramer 1.0000 0.05 -0.2614 0.3957 -0.5860 0.7203
hospbi*age_gr*sample B 9 1 C 9 1 0.000608 0.01681 30 0.04 0.9714 Tukey-Kramer 1.0000 0.05 -0.03372 0.03493 -0.06763 0.06884
hospbi*age_gr*sample B 9 1 A 9 2 0.05666 0.3120 30 0.18 0.8571 Tukey-Kramer 1.0000 0.05 -0.5806 0.6939 -1.2101 1.3234
hospbi*age_gr*sample B 9 1 B 9 2 0.05831 0.1107 30 0.53 0.6024 Tukey-Kramer 1.0000 0.05 -0.1679 0.2845 -0.3913 0.5079
hospbi*age_gr*sample B 9 1 C 9 2 0.05616 0.1403 30 0.40 0.6919 Tukey-Kramer 1.0000 0.05 -0.2305 0.3428 -0.5136 0.6260
hospbi*age_gr*sample B 9 1 A 9 3 0.05378 0.1196 30 0.45 0.6563 Tukey-Kramer 1.0000 0.05 -0.1906 0.2981 -0.4320 0.5395
hospbi*age_gr*sample B 9 1 B 9 3 0.05264 0.06066 30 0.87 0.3923 Tukey-Kramer 1.0000 0.05 -0.07123 0.1765 -0.1936 0.2989
hospbi*age_gr*sample B 9 1 C 9 3 0.04769 0.06789 30 0.70 0.4877 Tukey-Kramer 1.0000 0.05 -0.09095 0.1863 -0.2279 0.3233
hospbi*age_gr*sample C 9 1 A 9 2 0.05605 0.3150 30 0.18 0.8600 Tukey-Kramer 1.0000 0.05 -0.5872 0.6993 -1.2228 1.3349
hospbi*age_gr*sample C 9 1 B 9 2 0.05770 0.1188 30 0.49 0.6308 Tukey-Kramer 1.0000 0.05 -0.1850 0.3004 -0.4248 0.5402
hospbi*age_gr*sample C 9 1 C 9 2 0.05555 0.1468 30 0.38 0.7078 Tukey-Kramer 1.0000 0.05 -0.2443 0.3554 -0.5405 0.6516
hospbi*age_gr*sample C 9 1 A 9 3 0.05317 0.1272 30 0.42 0.6789 Tukey-Kramer 1.0000 0.05 -0.2066 0.3129 -0.4632 0.5695
hospbi*age_gr*sample C 9 1 B 9 3 0.05204 0.07441 30 0.70 0.4898 Tukey-Kramer 1.0000 0.05 -0.09994 0.2040 -0.2501 0.3542
hospbi*age_gr*sample C 9 1 C 9 3 0.04709 0.08042 30 0.59 0.5626 Tukey-Kramer 1.0000 0.05 -0.1171 0.2113 -0.2794 0.3736
hospbi*age_gr*sample A 9 2 B 9 2 0.001646 0.2116 30 0.01 0.9938 Tukey-Kramer 1.0000 0.05 -0.4305 0.4338 -0.8575 0.8607
hospbi*age_gr*sample A 9 2 C 9 2 -0.00050 0.1787 30 -0.00 0.9978 Tukey-Kramer 1.0000 0.05 -0.3654 0.3644 -0.7259 0.7249
hospbi*age_gr*sample A 9 2 A 9 3 -0.00288 0.3268 30 -0.01 0.9930 Tukey-Kramer 1.0000 0.05 -0.6702 0.6644 -1.3295 1.3237
hospbi*age_gr*sample A 9 2 B 9 3 -0.00401 0.3100 30 -0.01 0.9898 Tukey-Kramer 1.0000 0.05 -0.6372 0.6292 -1.2628 1.2548
hospbi*age_gr*sample A 9 2 C 9 3 -0.00897 0.3115 30 -0.03 0.9772 Tukey-Kramer 1.0000 0.05 -0.6452 0.6273 -1.2738 1.2559
hospbi*age_gr*sample B 9 2 C 9 2 -0.00215 0.03361 30 -0.06 0.9494 Tukey-Kramer 1.0000 0.05 -0.07080 0.06650 -0.1386 0.1343
hospbi*age_gr*sample B 9 2 A 9 3 -0.00453 0.1472 30 -0.03 0.9757 Tukey-Kramer 1.0000 0.05 -0.3052 0.2961 -0.6022 0.5932
hospbi*age_gr*sample B 9 2 B 9 3 -0.00566 0.1051 30 -0.05 0.9574 Tukey-Kramer 1.0000 0.05 -0.2202 0.2089 -0.4322 0.4209
hospbi*age_gr*sample B 9 2 C 9 3 -0.01061 0.1094 30 -0.10 0.9234 Tukey-Kramer 1.0000 0.05 -0.2340 0.2128 -0.4547 0.4335
hospbi*age_gr*sample C 9 2 A 9 3 -0.00238 0.1706 30 -0.01 0.9890 Tukey-Kramer 1.0000 0.05 -0.3508 0.3461 -0.6950 0.6903
hospbi*age_gr*sample C 9 2 B 9 3 -0.00351 0.1359 30 -0.03 0.9796 Tukey-Kramer 1.0000 0.05 -0.2811 0.2740 -0.5553 0.5483
hospbi*age_gr*sample C 9 2 C 9 3 -0.00846 0.1393 30 -0.06 0.9520 Tukey-Kramer 1.0000 0.05 -0.2929 0.2760 -0.5739 0.5570
hospbi*age_gr*sample A 9 3 B 9 3 -0.00113 0.07481 30 -0.02 0.9880 Tukey-Kramer 1.0000 0.05 -0.1539 0.1517 -0.3049 0.3026
hospbi*age_gr*sample A 9 3 C 9 3 -0.00609 0.06317 30 -0.10 0.9239 Tukey-Kramer 1.0000 0.05 -0.1351 0.1229 -0.2626 0.2504
hospbi*age_gr*sample B 9 3 C 9 3 -0.00495 0.01188 30 -0.42 0.6799 Tukey-Kramer 1.0000 0.05 -0.02922 0.01932 -0.05320 0.04330

data for supplemental table 2 and figure 1

In [25]:
/*ls means values by head body and tail*/

DATA dual_lsmeans1 (drop=age_group);
     set dual_lsmeans;
     if age_group^="" then delete;
     stain="dual           ";
     rename _NAME_=pancreas_region;
run;

PROC print data=dual_lsmeans1;
run;

/*grand mean values*/

PROC means data=dual_lsmeans1 mean;
     var lsmean;
     class hospbin;
     output out=dual_grandmean;
run;

DATA dual_grandmean (drop=_type_ _freq_ _stat_);
     set dual_grandmean;
     if _stat_^="MEAN" then delete;
     if hospbin="" then delete;
     pancreas_region="Overall";
     stain="dual           ";
run;

/*combine files into 1*/

DATA dual_fig1;
     set dual_lsmeans1 dual_grandmean;
run;

PROC print data=dual_fig1;
run;
Out[25]:
SAS Output
Obs pancreas_region hospbin LSMEAN stain
1 Head 3 0.23147 dual
2 Head 6 0.01599 dual
3 Head 9 0.02948 dual
4 Body 3 0.07504 dual
5 Body 6 0.01402 dual
6 Body 9 0.02283 dual
7 Tail 3 0.10131 dual
8 Tail 6 0.02550 dual
9 Tail 9 0.02499 dual

The MEANS Procedure

Analysis Variable : LSMEAN
hospbin N Obs Mean
3 3 0.1359428
6 3 0.0185024
9 3 0.0257684

Obs pancreas_region hospbin LSMEAN stain
1 Head 3 0.23147 dual
2 Head 6 0.01599 dual
3 Head 9 0.02948 dual
4 Body 3 0.07504 dual
5 Body 6 0.01402 dual
6 Body 9 0.02283 dual
7 Tail 3 0.10131 dual
8 Tail 6 0.02550 dual
9 Tail 9 0.02499 dual
10 Overall 3 0.13594 dual
11 Overall 6 0.01850 dual
12 Overall 9 0.02577 dual

All datasets

data for figure 1

In [26]:
DATA figure1;
     set cd45_fig1 cd68_fig1 insulin1_fig1 ki67_fig1 dual_fig1;
run;

proc print data=figure1;
run;

PROC export data=figure1 
     outfile="figure1.csv" 
     dbms=csv
     replace;
run; 
Out[26]:
SAS Output
Obs pancreas_region hospbin LSMEAN stain
1 Head 3 3.97633 CD45
2 Head 6 3.64362 CD45
3 Head 9 4.86435 CD45
4 Body 3 4.21742 CD45
5 Body 6 4.17156 CD45
6 Body 9 4.61384 CD45
7 Tail 3 5.35137 CD45
8 Tail 6 4.70966 CD45
9 Tail 9 5.66880 CD45
10 Overall 3 4.51504 CD45
11 Overall 6 4.17495 CD45
12 Overall 9 5.04900 CD45
13 Head 3 2.11729 CD68
14 Head 6 2.11608 CD68
15 Head 9 3.43758 CD68
16 Body 3 2.81909 CD68
17 Body 6 2.58786 CD68
18 Body 9 3.18992 CD68
19 Tail 3 2.81956 CD68
20 Tail 6 2.41701 CD68
21 Tail 9 3.80707 CD68
22 Overall 3 2.58531 CD68
23 Overall 6 2.37365 CD68
24 Overall 9 3.47819 CD68
25 Head 3 3.67605 Insulin
26 Head 6 2.59539 Insulin
27 Head 9 2.25901 Insulin
28 Body 3 2.97310 Insulin
29 Body 6 2.22844 Insulin
30 Body 9 2.07233 Insulin
31 Tail 3 3.54317 Insulin
32 Tail 6 3.19101 Insulin
33 Tail 9 2.69677 Insulin
34 Overall 3 3.39744 Insulin
35 Overall 6 2.67161 Insulin
36 Overall 9 2.34270 Insulin
37 Head 3 1.48995 Ki67
38 Head 6 0.50260 Ki67
39 Head 9 1.93662 Ki67
40 Body 3 1.70602 Ki67
41 Body 6 0.67179 Ki67
42 Body 9 1.75012 Ki67
43 Tail 3 1.41474 Ki67
44 Tail 6 0.58658 Ki67
45 Tail 9 1.58369 Ki67
46 Overall 3 1.53690 Ki67
47 Overall 6 0.58699 Ki67
48 Overall 9 1.75681 Ki67
49 Head 3 0.23147 dual
50 Head 6 0.01599 dual
51 Head 9 0.02948 dual
52 Body 3 0.07504 dual
53 Body 6 0.01402 dual
54 Body 9 0.02283 dual
55 Tail 3 0.10131 dual
56 Tail 6 0.02550 dual
57 Tail 9 0.02499 dual
58 Overall 3 0.13594 dual
59 Overall 6 0.01850 dual
60 Overall 9 0.02577 dual

ESM Figure 1 interaction plot panel for hospitalization time by age group interaction

In [30]:
proc print data=cd45_mean;
run;

proc print data=insulin_mean;
run;
Out[30]:
SAS Output
Obs Case hospbin age_group oppc_ageR mean_pancreas
1 6106 3 1 2.9 2.0916933333
2 6200 3 1 0.0065753425 4.98828
3 6278 3 1 10 4.0959133333
4 6073 3 2 19.2 9.17934
5 6099 3 2 14.2 2.9321966667
6 6003 3 3 23 2.6214733333
7 6048 3 3 30 1.3001633333
8 6131 3 3 24.2 4.40351
9 6134 3 3 26.7 2.6490233333
10 6162 3 3 22.7 2.2208266667
11 6174 3 3 20.8 1.6876333333
12 6235 3 3 30 5.6687266667
13 6250 3 3 40 9.5611333333
14 6047 6 1 7.8 4.04501
15 6117 6 1 0.33 5.01601
16 6187 6 1 0.33 1.9342333333
17 6219 6 1 0.5 7.56861
18 6230 6 2 16 0.490014
19 6279 6 2 19 3.2508066667
20 6104 6 3 41 0.9583076667
21 6126 6 3 25.2 14.760666667
22 6129 6 3 42.9 3.2638666667
23 6165 6 3 45.8 6.8778533333
24 6229 6 3 31 3.26601
25 6251 6 3 33 5.5635466667
26 6254 6 3 38 7.4039733333
27 6005 9 1 5 3.98069
28 6007 9 1 9 4.7147633333
29 6115 9 1 0.42 9.6911466667
30 6144 9 1 7.5 1.8678786667
31 6172 9 2 19.2 3.6092633333
32 6008 9 3 50 3.18315
33 6011 9 3 46 11.626993333
34 6019 9 3 42 1.72115
35 6057 9 3 22 3.00143
36 6060 9 3 24 4.73816
37 6140 9 3 38 13.99183
38 6178 9 3 24.5 5.2902
39 6179 9 3 21.8 8.23996

Obs Case hospbin age_group oppc_ageR mean_pancreas
1 6106 3 1 2.9 2.6593095556
2 6200 3 1 0.0065753425 15.456781111
3 6278 3 1 10 2.9618144444
4 6073 3 2 19.2 1.4437288889
5 6099 3 2 14.2 1.8993911111
6 6003 3 3 23 2.2689211111
7 6048 3 3 30 1.3639012222
8 6131 3 3 24.2 2.0004911111
9 6134 3 3 26.7 1.0221464444
10 6162 3 3 22.7 1.0960842222
11 6174 3 3 20.8 1.399986
12 6235 3 3 30 0.9941592222
13 6250 3 3 40 1.8127255556
14 6047 6 1 7.8 1.6661255556
15 6117 6 1 0.33 4.709714
16 6187 6 1 0.33 8.6629144444
17 6219 6 1 0.5 4.2083188889
18 6230 6 2 16 0.985314
19 6279 6 2 19 2.4339522222
20 6104 6 3 41 1.0314343333
21 6126 6 3 25.2 1.0116701111
22 6129 6 3 42.9 1.6572622222
23 6165 6 3 45.8 0.7123386667
24 6229 6 3 31 3.1872377778
25 6251 6 3 33 1.0449202222
26 6254 6 3 38 1.8091744444
27 6005 9 1 5 2.3486111111
28 6007 9 1 9 1.7416066667
29 6115 9 1 0.42 5.2413955556
30 6144 9 1 7.5 2.1990355556
31 6172 9 2 19.2 2.6835566667
32 6008 9 3 50 0.7538947778
33 6011 9 3 46 2.0067311111
34 6019 9 3 42 1.5802324444
35 6057 9 3 22 2.3994888889
36 6060 9 3 24 1.4650126667
37 6140 9 3 38 1.3753716667
38 6178 9 3 24.5 1.2414216667
39 6179 9 3 21.8 0.8729275556
In [27]:
/*to determine a mean value for each combination of hospitalization by age group combination*/

%mean(cd45,percent_cd45);
PROC sort data=cd45_mean;
     by hospbin age_group;
run;
PROC univariate data=cd45_mean;
     by hospbin age_group;
     var mean_pancreas;
     output out=cd45_interaction mean=mean_pancreas_group;
run;
DATA cd45_interaction;
     set cd45_interaction;
     dataset="CD45      ";
run;

%mean(cd68,percent_cd68);
PROC sort data=cd68_mean;
     by hospbin age_group;
run;
PROC univariate data=cd68_mean;
     by hospbin age_group;
     var mean_pancreas;
     output out=cd68_interaction mean=mean_pancreas_group;
run;
DATA cd68_interaction;
     set cd68_interaction;
     dataset="CD68      ";
run;

%mean(insulin,percent_insulin);
PROC sort data=insulin_mean;
     by hospbin age_group;
run;
PROC univariate data=insulin_mean;
     by hospbin age_group;
     var mean_pancreas;
     output out=insulin_interaction mean=mean_pancreas_group;
run;
DATA insulin_interaction;
     set insulin_interaction;
     dataset="Insulin(I)   ";
run;

%mean(ki67,percent_ki67);
PROC sort data=ki67_mean;
     by hospbin age_group;
run;
PROC univariate data=ki67_mean;
     by hospbin age_group;
     var mean_pancreas;
     output out=ki67_interaction mean=mean_pancreas_group;
run;
DATA ki67_interaction;
     set ki67_interaction;
     dataset="Ki67      ";
run;
 
/*did not use macro for dual dataset*/
PROC means data=ki67 nway noprint;
     class case hospbin age_group oppc_ageR;
     var percent_dual;
     output out=ki67dual_mean (drop=_type_ _freq_) mean=mean_pancreas;
run;
PROC sort data=ki67dual_mean;
     by hospbin age_group;
run;
PROC univariate data=ki67dual_mean;
     by hospbin age_group;
     var mean_pancreas;
     output out=ki67dual_interaction mean=mean_pancreas_group;
run;
DATA ki67dual_interaction;
     set ki67dual_interaction;
     dataset="Ki67+I     ";
run;

DATA all_interactions;
     set cd45_interaction cd68_interaction insulin_interaction ki67_interaction ki67dual_interaction;
run;
 
PROC print data=all_interactions;
run;

ODS GRAPHICS ON / reset = all height= 4 in width=7 in border= off imagename="ESM_Fig1";
ods listing image_dpi=600;

PROC sgpanel data=all_interactions noautolegend;
     panelby dataset/novarname noheaderborder headerbackcolor=white headerattrs=(size=16pt Family=Arial) onepanel;
     format hospbin hospname. age_group agename.;
     series x=hospbin y=mean_pancreas_group/ group=age_group name="Lines" LINEATTRS = (THICKNESS = 2.0 pattern=solid);
     styleattrs datacontrastcolors=(cx8AA9D6 cxC04140 cx6DA567);
     colaxis values=(3 to 9 by 3) discreteorder=data labelattrs=(size=16) valueattrs=(size=16 Family=Arial) label="Days in hospital prior to organ donation" labelattrs=(size = 16 weight=bold Family=Arial);
     rowaxis values=(0 to 6 by 1) labelattrs=(size=16) valueattrs=(size=16 Family=Arial) label="Positive cells (%)" labelattrs=(size = 16 weight=bold Family=Arial);
     /*keylegend "Lines"/title= "Age Group" titleattrs=(size=16) titleattrs=(weight=bold) valueattrs=(size=16) valueattrs=(weight=bold) noborder position=right*/;
run;

ODS graphics off;
Out[27]:
SAS Output

The UNIVARIATE Procedure

Variable: mean_pancreas (% CD45 Positive Cells)

Moments
N 3 Sum Weights 3
Mean 3.72529556 Sum Observations 11.1758867
Std Deviation 1.48343242 Variance 2.20057173
Skewness -1.0540951 Kurtosis .
Uncorrected SS 46.0346244 Corrected SS 4.40114346
Coeff Variation 39.8205295 Std Error Mean 0.8564601
Basic Statistical Measures
Location Variability
Mean 3.725296 Std Deviation 1.48343
Median 4.095913 Variance 2.20057
Mode . Range 2.89659
    Interquartile Range 2.89659
Tests for Location: Mu0=0
Test Statistic p Value
Student's t t 4.349643 Pr > |t| 0.0490
Sign M 1.5 Pr >= |M| 0.2500
Signed Rank S 3 Pr >= |S| 0.2500
Quantiles (Definition 5)
Level Quantile
100% Max 4.98828
99% 4.98828
95% 4.98828
90% 4.98828
75% Q3 4.98828
50% Median 4.09591
25% Q1 2.09169
10% 2.09169
5% 2.09169
1% 2.09169
0% Min 2.09169
Extreme Observations
Lowest Highest
Value Obs Value Obs
2.09169 1 2.09169 1
4.09591 3 4.09591 3
4.98828 2 4.98828 2

The UNIVARIATE Procedure

Variable: mean_pancreas (% CD45 Positive Cells)

Moments
N 2 Sum Weights 2
Mean 6.05576833 Sum Observations 12.1115367
Std Deviation 4.41739741 Variance 19.5133999
Skewness . Kurtosis .
Uncorrected SS 92.8580601 Corrected SS 19.5133999
Coeff Variation 72.9452841 Std Error Mean 3.12357167
Basic Statistical Measures
Location Variability
Mean 6.055768 Std Deviation 4.41740
Median 6.055768 Variance 19.51340
Mode . Range 6.24714
    Interquartile Range 6.24714
Tests for Location: Mu0=0
Test Statistic p Value
Student's t t 1.938732 Pr > |t| 0.3032
Sign M 1 Pr >= |M| 0.5000
Signed Rank S 1.5 Pr >= |S| 0.5000
Quantiles (Definition 5)
Level Quantile
100% Max 9.17934
99% 9.17934
95% 9.17934
90% 9.17934
75% Q3 9.17934
50% Median 6.05577
25% Q1 2.93220
10% 2.93220
5% 2.93220
1% 2.93220
0% Min 2.93220
Extreme Observations
Lowest Highest
Value Obs Value Obs
2.93220 5 2.93220 5
9.17934 4 9.17934 4

The UNIVARIATE Procedure

Variable: mean_pancreas (% CD45 Positive Cells)

Moments
N 8 Sum Weights 8
Mean 3.76406125 Sum Observations 30.11249
Std Deviation 2.75046555 Variance 7.56506076
Skewness 1.57017121 Kurtosis 2.33131449
Uncorrected SS 166.300682 Corrected SS 52.9554253
Coeff Variation 73.0717534 Std Error Mean 0.97243642
Basic Statistical Measures
Location Variability
Mean 3.764061 Std Deviation 2.75047
Median 2.635248 Variance 7.56506
Mode . Range 8.26097
    Interquartile Range 3.08189
Tests for Location: Mu0=0
Test Statistic p Value
Student's t t 3.870753 Pr > |t| 0.0061
Sign M 4 Pr >= |M| 0.0078
Signed Rank S 18 Pr >= |S| 0.0078
Quantiles (Definition 5)
Level Quantile
100% Max 9.56113
99% 9.56113
95% 9.56113
90% 9.56113
75% Q3 5.03612
50% Median 2.63525
25% Q1 1.95423
10% 1.30016
5% 1.30016
1% 1.30016
0% Min 1.30016
Extreme Observations
Lowest Highest
Value Obs Value Obs
1.30016 7 2.62147 6
1.68763 11 2.64902 9
2.22083 10 4.40351 8
2.62147 6 5.66873 12
2.64902 9 9.56113 13

The UNIVARIATE Procedure

Variable: mean_pancreas (% CD45 Positive Cells)

Moments
N 4 Sum Weights 4
Mean 4.64096583 Sum Observations 18.5638633
Std Deviation 2.33761436 Variance 5.46444089
Skewness 0.26635947 Kurtosis 0.70912583
Uncorrected SS 102.547578 Corrected SS 16.3933227
Coeff Variation 50.3691353 Std Error Mean 1.16880718
Basic Statistical Measures
Location Variability
Mean 4.640966 Std Deviation 2.33761
Median 4.530510 Variance 5.46444
Mode . Range 5.63438
    Interquartile Range 3.30269
Tests for Location: Mu0=0
Test Statistic p Value
Student's t t 3.970686 Pr > |t| 0.0286
Sign M 2 Pr >= |M| 0.1250
Signed Rank S 5 Pr >= |S| 0.1250
Quantiles (Definition 5)
Level Quantile
100% Max 7.56861
99% 7.56861
95% 7.56861
90% 7.56861
75% Q3 6.29231
50% Median 4.53051
25% Q1 2.98962
10% 1.93423
5% 1.93423
1% 1.93423
0% Min 1.93423
Extreme Observations
Lowest Highest
Value Obs Value Obs
1.93423 16 1.93423 16
4.04501 14 4.04501 14
5.01601 15 5.01601 15
7.56861 17 7.56861 17

The UNIVARIATE Procedure

Variable: mean_pancreas (% CD45 Positive Cells)

Moments
N 2 Sum Weights 2
Mean 1.87041033 Sum Observations 3.74082067
Std Deviation 1.95217522 Variance 3.81098807
Skewness . Kurtosis .
Uncorrected SS 10.8078577 Corrected SS 3.81098807
Coeff Variation 104.371494 Std Error Mean 1.38039633
Basic Statistical Measures
Location Variability
Mean 1.870410 Std Deviation 1.95218
Median 1.870410 Variance 3.81099
Mode . Range 2.76079
    Interquartile Range 2.76079
Tests for Location: Mu0=0
Test Statistic p Value
Student's t t 1.354981 Pr > |t| 0.4048
Sign M 1 Pr >= |M| 0.5000
Signed Rank S 1.5 Pr >= |S| 0.5000
Quantiles (Definition 5)
Level Quantile
100% Max 3.250807
99% 3.250807
95% 3.250807
90% 3.250807
75% Q3 3.250807
50% Median 1.870410
25% Q1 0.490014
10% 0.490014
5% 0.490014
1% 0.490014
0% Min 0.490014
Extreme Observations
Lowest Highest
Value Obs Value Obs
0.490014 18 0.490014 18
3.250807 19 3.250807 19

The UNIVARIATE Procedure

Variable: mean_pancreas (% CD45 Positive Cells)

Moments
N 7 Sum Weights 7
Mean 6.01346062 Sum Observations 42.0942243
Std Deviation 4.47325496 Variance 20.01001
Skewness 1.30812487 Kurtosis 2.32241954
Uncorrected SS 373.19202 Corrected SS 120.06006
Coeff Variation 74.387366 Std Error Mean 1.69073145
Basic Statistical Measures
Location Variability
Mean 6.013461 Std Deviation 4.47325
Median 5.563547 Variance 20.01001
Mode . Range 13.80236
    Interquartile Range 4.14011
Tests for Location: Mu0=0
Test Statistic p Value
Student's t t 3.556721 Pr > |t| 0.0120
Sign M 3.5 Pr >= |M| 0.0156
Signed Rank S 14 Pr >= |S| 0.0156
Quantiles (Definition 5)
Level Quantile
100% Max 14.760667
99% 14.760667
95% 14.760667
90% 14.760667
75% Q3 7.403973
50% Median 5.563547
25% Q1 3.263867
10% 0.958308
5% 0.958308
1% 0.958308
0% Min 0.958308
Extreme Observations
Lowest Highest
Value Obs Value Obs
0.958308 20 3.26601 24
3.263867 22 5.56355 25
3.266010 24 6.87785 23
5.563547 25 7.40397 26
6.877853 23 14.76067 21

The UNIVARIATE Procedure

Variable: mean_pancreas (% CD45 Positive Cells)

Moments
N 4 Sum Weights 4
Mean 5.06361967 Sum Observations 20.2544787
Std Deviation 3.31266278 Variance 10.9737347
Skewness 1.19468164 Kurtosis 2.11858192
Uncorrected SS 135.482181 Corrected SS 32.9212041
Coeff Variation 65.4208451 Std Error Mean 1.65633139
Basic Statistical Measures
Location Variability
Mean 5.063620 Std Deviation 3.31266
Median 4.347727 Variance 10.97373
Mode . Range 7.82327
    Interquartile Range 4.27867
Tests for Location: Mu0=0
Test Statistic p Value
Student's t t 3.05713 Pr > |t| 0.0551
Sign M 2 Pr >= |M| 0.1250
Signed Rank S 5 Pr >= |S| 0.1250
Quantiles (Definition 5)
Level Quantile
100% Max 9.69115
99% 9.69115
95% 9.69115
90% 9.69115
75% Q3 7.20296
50% Median 4.34773
25% Q1 2.92428
10% 1.86788
5% 1.86788
1% 1.86788
0% Min 1.86788
Extreme Observations
Lowest Highest
Value Obs Value Obs
1.86788 30 1.86788 30
3.98069 27 3.98069 27
4.71476 28 4.71476 28
9.69115 29 9.69115 29

The UNIVARIATE Procedure

Variable: mean_pancreas (% CD45 Positive Cells)

Moments
N 1 Sum Weights 1
Mean 3.60926333 Sum Observations 3.60926333
Std Deviation . Variance .
Skewness . Kurtosis .
Uncorrected SS 13.0267818 Corrected SS 0
Coeff Variation . Std Error Mean .
Basic Statistical Measures
Location Variability
Mean 3.609263 Std Deviation .
Median 3.609263 Variance .
Mode 3.609263 Range 0
    Interquartile Range 0
Tests for Location: Mu0=0
Test Statistic p Value
Student's t t . Pr > |t| .
Sign M 0.5 Pr >= |M| 1.0000
Signed Rank S 0.5 Pr >= |S| 1.0000
Quantiles (Definition 5)
Level Quantile
100% Max 3.60926
99% 3.60926
95% 3.60926
90% 3.60926
75% Q3 3.60926
50% Median 3.60926
25% Q1 3.60926
10% 3.60926
5% 3.60926
1% 3.60926
0% Min 3.60926
Extreme Observations
Lowest Highest
Value Obs Value Obs
3.60926 31 3.60926 31

The UNIVARIATE Procedure

Variable: mean_pancreas (% CD45 Positive Cells)

Moments
N 8 Sum Weights 8
Mean 6.47410917 Sum Observations 51.7928733
Std Deviation 4.40911823 Variance 19.4403236
Skewness 0.83425173 Kurtosis -0.642545
Uncorrected SS 471.394981 Corrected SS 136.082265
Coeff Variation 68.1038598 Std Error Mean 1.5588587
Basic Statistical Measures
Location Variability
Mean 6.474109 Std Deviation 4.40912
Median 5.014180 Variance 19.44032
Mode . Range 12.27068
    Interquartile Range 6.84119
Tests for Location: Mu0=0
Test Statistic p Value
Student's t t 4.153108 Pr > |t| 0.0043
Sign M 4 Pr >= |M| 0.0078
Signed Rank S 18 Pr >= |S| 0.0078
Quantiles (Definition 5)
Level Quantile
100% Max 13.99183
99% 13.99183
95% 13.99183
90% 13.99183
75% Q3 9.93348
50% Median 5.01418
25% Q1 3.09229
10% 1.72115
5% 1.72115
1% 1.72115
0% Min 1.72115
Extreme Observations
Lowest Highest
Value Obs Value Obs
1.72115 34 4.73816 36
3.00143 35 5.29020 38
3.18315 32 8.23996 39
4.73816 36 11.62699 33
5.29020 38 13.99183 37

The UNIVARIATE Procedure

Variable: mean_pancreas (% CD68 Positive Cells)

Moments
N 3 Sum Weights 3
Mean 1.71937922 Sum Observations 5.15813767
Std Deviation 0.96227553 Variance 0.9259742
Skewness 1.20967313 Kurtosis .
Uncorrected SS 10.7207431 Corrected SS 1.85194839
Coeff Variation 55.966451 Std Error Mean 0.55557004
Basic Statistical Measures
Location Variability
Mean 1.719379 Std Deviation 0.96228
Median 1.436173 Variance 0.92597
Mode . Range 1.86099
    Interquartile Range 1.86099
Tests for Location: Mu0=0
Test Statistic p Value
Student's t t 3.094802 Pr > |t| 0.0905
Sign M 1.5 Pr >= |M| 0.2500
Signed Rank S 3 Pr >= |S| 0.2500
Quantiles (Definition 5)
Level Quantile
100% Max 2.791477
99% 2.791477
95% 2.791477
90% 2.791477
75% Q3 2.791477
50% Median 1.436173
25% Q1 0.930488
10% 0.930488
5% 0.930488
1% 0.930488
0% Min 0.930488
Extreme Observations
Lowest Highest
Value Obs Value Obs
0.930488 1 0.930488 1
1.436173 3 1.436173 3
2.791477 2 2.791477 2

The UNIVARIATE Procedure

Variable: mean_pancreas (% CD68 Positive Cells)

Moments
N 2 Sum Weights 2
Mean 4.50595283 Sum Observations 9.01190567
Std Deviation 5.46995721 Variance 29.9204318
Skewness . Kurtosis .
Uncorrected SS 70.5276537 Corrected SS 29.9204318
Coeff Variation 121.394018 Std Error Mean 3.86784383
Basic Statistical Measures
Location Variability
Mean 4.505953 Std Deviation 5.46996
Median 4.505953 Variance 29.92043
Mode . Range 7.73569
    Interquartile Range 7.73569
Tests for Location: Mu0=0
Test Statistic p Value
Student's t t 1.164978 Pr > |t| 0.4516
Sign M 1 Pr >= |M| 0.5000
Signed Rank S 1.5 Pr >= |S| 0.5000
Quantiles (Definition 5)
Level Quantile
100% Max 8.373797
99% 8.373797
95% 8.373797
90% 8.373797
75% Q3 8.373797
50% Median 4.505953
25% Q1 0.638109
10% 0.638109
5% 0.638109
1% 0.638109
0% Min 0.638109
Extreme Observations
Lowest Highest
Value Obs Value Obs
0.638109 5 0.638109 5
8.373797 4 8.373797 4

The UNIVARIATE Procedure

Variable: mean_pancreas (% CD68 Positive Cells)

Moments
N 8 Sum Weights 8
Mean 1.53060575 Sum Observations 12.244846
Std Deviation 1.5034751 Variance 2.26043738
Skewness 1.574963 Kurtosis 2.68492458
Uncorrected SS 34.5650933 Corrected SS 15.8230616
Coeff Variation 98.2274567 Std Error Mean 0.53155872
Basic Statistical Measures
Location Variability
Mean 1.530606 Std Deviation 1.50348
Median 1.073553 Variance 2.26044
Mode . Range 4.37085
    Interquartile Range 1.63279
Tests for Location: Mu0=0
Test Statistic p Value
Student's t t 2.879467 Pr > |t| 0.0237
Sign M 4 Pr >= |M| 0.0078
Signed Rank S 18 Pr >= |S| 0.0078
Quantiles (Definition 5)
Level Quantile
100% Max 4.745687
99% 4.745687
95% 4.745687
90% 4.745687
75% Q3 2.060700
50% Median 1.073553
25% Q1 0.427906
10% 0.374841
5% 0.374841
1% 0.374841
0% Min 0.374841
Extreme Observations
Lowest Highest
Value Obs Value Obs
0.374841 10 0.466089 11
0.409039 9 1.681017 12
0.446774 7 2.053593 8
0.466089 11 2.067807 6
1.681017 12 4.745687 13

The UNIVARIATE Procedure

Variable: mean_pancreas (% CD68 Positive Cells)

Moments
N 4 Sum Weights 4
Mean 2.97854883 Sum Observations 11.9141953
Std Deviation 1.71997358 Variance 2.95830912
Skewness -0.3525607 Kurtosis 0.54797299
Uncorrected SS 44.36194 Corrected SS 8.87492735
Coeff Variation 57.7453544 Std Error Mean 0.85998679
Basic Statistical Measures
Location Variability
Mean 2.978549 Std Deviation 1.71997
Median 3.088070 Variance 2.95831
Mode . Range 4.12513
    Interquartile Range 2.46169
Tests for Location: Mu0=0
Test Statistic p Value
Student's t t 3.463482 Pr > |t| 0.0405
Sign M 2 Pr >= |M| 0.1250
Signed Rank S 5 Pr >= |S| 0.1250
Quantiles (Definition 5)
Level Quantile
100% Max 4.931593
99% 4.931593
95% 4.931593
90% 4.931593
75% Q3 4.209392
50% Median 3.088070
25% Q1 1.747706
10% 0.806462
5% 0.806462
1% 0.806462
0% Min 0.806462
Extreme Observations
Lowest Highest
Value Obs Value Obs
0.806462 16 0.806462 16
2.688950 14 2.688950 14
3.487190 15 3.487190 15
4.931593 17 4.931593 17

The UNIVARIATE Procedure

Variable: mean_pancreas (% CD68 Positive Cells)

Moments
N 2 Sum Weights 2
Mean 1.1544425 Sum Observations 2.308885
Std Deviation 0.92793269 Variance 0.86105908
Skewness . Kurtosis .
Uncorrected SS 3.52653406 Corrected SS 0.86105908
Coeff Variation 80.3792907 Std Error Mean 0.6561475
Basic Statistical Measures
Location Variability
Mean 1.154443 Std Deviation 0.92793
Median 1.154443 Variance 0.86106
Mode . Range 1.31230
    Interquartile Range 1.31230
Tests for Location: Mu0=0
Test Statistic p Value
Student's t t 1.759425 Pr > |t| 0.3290
Sign M 1 Pr >= |M| 0.5000
Signed Rank S 1.5 Pr >= |S| 0.5000
Quantiles (Definition 5)
Level Quantile
100% Max 1.810590
99% 1.810590
95% 1.810590
90% 1.810590
75% Q3 1.810590
50% Median 1.154443
25% Q1 0.498295
10% 0.498295
5% 0.498295
1% 0.498295
0% Min 0.498295
Extreme Observations
Lowest Highest
Value Obs Value Obs
0.498295 18 0.498295 18
1.810590 19 1.810590 19

The UNIVARIATE Procedure

Variable: mean_pancreas (% CD68 Positive Cells)

Moments
N 7 Sum Weights 7
Mean 2.98795619 Sum Observations 20.9156933
Std Deviation 1.81754752 Variance 3.303479
Skewness 1.33456756 Kurtosis 2.16635512
Uncorrected SS 82.3160494 Corrected SS 19.820874
Coeff Variation 60.8291223 Std Error Mean 0.68696839
Basic Statistical Measures
Location Variability
Mean 2.987956 Std Deviation 1.81755
Median 3.131857 Variance 3.30348
Mode . Range 5.32471
    Interquartile Range 1.99988
Tests for Location: Mu0=0
Test Statistic p Value
Student's t t 4.349481 Pr > |t| 0.0048
Sign M 3.5 Pr >= |M| 0.0156
Signed Rank S 14 Pr >= |S| 0.0156
Quantiles (Definition 5)
Level Quantile
100% Max 6.54303
99% 6.54303
95% 6.54303
90% 6.54303
75% Q3 3.46266
50% Median 3.13186
25% Q1 1.46278
10% 1.21832
5% 1.21832
1% 1.21832
0% Min 1.21832
Extreme Observations
Lowest Highest
Value Obs Value Obs
1.21832 24 1.80950 22
1.46278 25 3.13186 23
1.80950 22 3.28754 26
3.13186 23 3.46266 20
3.28754 26 6.54303 21

The UNIVARIATE Procedure

Variable: mean_pancreas (% CD68 Positive Cells)

Moments
N 4 Sum Weights 4
Mean 4.73336508 Sum Observations 18.9334603
Std Deviation 4.91191201 Variance 24.1268796
Skewness 1.60857886 Kurtosis 3.02507669
Uncorrected SS 161.999619 Corrected SS 72.3806389
Coeff Variation 103.772093 Std Error Mean 2.45595601
Basic Statistical Measures
Location Variability
Mean 4.733365 Std Deviation 4.91191
Median 3.227805 Variance 24.12688
Mode . Range 11.25268
    Interquartile Range 5.66067
Tests for Location: Mu0=0
Test Statistic p Value
Student's t t 1.9273 Pr > |t| 0.1496
Sign M 2 Pr >= |M| 0.1250
Signed Rank S 5 Pr >= |S| 0.1250
Quantiles (Definition 5)
Level Quantile
100% Max 11.865267
99% 11.865267
95% 11.865267
90% 11.865267
75% Q3 7.563700
50% Median 3.227805
25% Q1 1.903030
10% 0.612584
5% 0.612584
1% 0.612584
0% Min 0.612584
Extreme Observations
Lowest Highest
Value Obs Value Obs
0.612584 30 0.612584 30
3.193477 29 3.193477 29
3.262133 27 3.262133 27
11.865267 28 11.865267 28

The UNIVARIATE Procedure

Variable: mean_pancreas (% CD68 Positive Cells)

Moments
N 1 Sum Weights 1
Mean 1.44924667 Sum Observations 1.44924667
Std Deviation . Variance .
Skewness . Kurtosis .
Uncorrected SS 2.1003159 Corrected SS 0
Coeff Variation . Std Error Mean .
Basic Statistical Measures
Location Variability
Mean 1.449247 Std Deviation .
Median 1.449247 Variance .
Mode 1.449247 Range 0
    Interquartile Range 0
Tests for Location: Mu0=0
Test Statistic p Value
Student's t t . Pr > |t| .
Sign M 0.5 Pr >= |M| 1.0000
Signed Rank S 0.5 Pr >= |S| 1.0000
Quantiles (Definition 5)
Level Quantile
100% Max 1.44925
99% 1.44925
95% 1.44925
90% 1.44925
75% Q3 1.44925
50% Median 1.44925
25% Q1 1.44925
10% 1.44925
5% 1.44925
1% 1.44925
0% Min 1.44925
Extreme Observations
Lowest Highest
Value Obs Value Obs
1.44925 31 1.44925 31

The UNIVARIATE Procedure

Variable: mean_pancreas (% CD68 Positive Cells)

Moments
N 8 Sum Weights 8
Mean 4.25196292 Sum Observations 34.0157033
Std Deviation 2.54826841 Variance 6.49367188
Skewness 0.52611068 Kurtosis -1.8227294
Uncorrected SS 190.089212 Corrected SS 45.4557031
Coeff Variation 59.9315765 Std Error Mean 0.90094894
Basic Statistical Measures
Location Variability
Mean 4.251963 Std Deviation 2.54827
Median 3.199365 Variance 6.49367
Mode . Range 6.18168
    Interquartile Range 4.58844
Tests for Location: Mu0=0
Test Statistic p Value
Student's t t 4.719427 Pr > |t| 0.0022
Sign M 4 Pr >= |M| 0.0078
Signed Rank S 18 Pr >= |S| 0.0078
Quantiles (Definition 5)
Level Quantile
100% Max 8.06031
99% 8.06031
95% 8.06031
90% 8.06031
75% Q3 6.71373
50% Median 3.19937
25% Q1 2.12529
10% 1.87863
5% 1.87863
1% 1.87863
0% Min 1.87863
Extreme Observations
Lowest Highest
Value Obs Value Obs
1.87863 38 2.26100 34
2.04645 32 4.13773 36
2.20412 35 6.42735 37
2.26100 34 7.00010 39
4.13773 36 8.06031 33

The UNIVARIATE Procedure

Variable: mean_pancreas (% Insulin Positive Cells)

Moments
N 3 Sum Weights 3
Mean 7.02596837 Sum Observations 21.0779051
Std Deviation 7.3028645 Variance 53.3318299
Skewness 1.72870798 Kurtosis .
Uncorrected SS 254.756354 Corrected SS 106.66366
Coeff Variation 103.941039 Std Error Mean 4.21631078
Basic Statistical Measures
Location Variability
Mean 7.025968 Std Deviation 7.30286
Median 2.961814 Variance 53.33183
Mode . Range 12.79747
    Interquartile Range 12.79747
Tests for Location: Mu0=0
Test Statistic p Value
Student's t t 1.666378 Pr > |t| 0.2376
Sign M 1.5 Pr >= |M| 0.2500
Signed Rank S 3 Pr >= |S| 0.2500
Quantiles (Definition 5)
Level Quantile
100% Max 15.45678
99% 15.45678
95% 15.45678
90% 15.45678
75% Q3 15.45678
50% Median 2.96181
25% Q1 2.65931
10% 2.65931
5% 2.65931
1% 2.65931
0% Min 2.65931
Extreme Observations
Lowest Highest
Value Obs Value Obs
2.65931 1 2.65931 1
2.96181 3 2.96181 3
15.45678 2 15.45678 2

The UNIVARIATE Procedure

Variable: mean_pancreas (% Insulin Positive Cells)

Moments
N 2 Sum Weights 2
Mean 1.67156 Sum Observations 3.34312
Std Deviation 0.32220185 Variance 0.10381403
Skewness . Kurtosis .
Uncorrected SS 5.6920397 Corrected SS 0.10381403
Coeff Variation 19.2755179 Std Error Mean 0.22783111
Basic Statistical Measures
Location Variability
Mean 1.671560 Std Deviation 0.32220
Median 1.671560 Variance 0.10381
Mode . Range 0.45566
    Interquartile Range 0.45566
Tests for Location: Mu0=0
Test Statistic p Value
Student's t t 7.336838 Pr > |t| 0.0862
Sign M 1 Pr >= |M| 0.5000
Signed Rank S 1.5 Pr >= |S| 0.5000
Quantiles (Definition 5)
Level Quantile
100% Max 1.89939
99% 1.89939
95% 1.89939
90% 1.89939
75% Q3 1.89939
50% Median 1.67156
25% Q1 1.44373
10% 1.44373
5% 1.44373
1% 1.44373
0% Min 1.44373
Extreme Observations
Lowest Highest
Value Obs Value Obs
1.44373 4 1.44373 4
1.89939 5 1.89939 5

The UNIVARIATE Procedure

Variable: mean_pancreas (% Insulin Positive Cells)

Moments
N 8 Sum Weights 8
Mean 1.49480186 Sum Observations 11.9584149
Std Deviation 0.48035771 Variance 0.23074353
Skewness 0.56330653 Kurtosis -1.2094945
Uncorrected SS 19.4906655 Corrected SS 1.61520468
Coeff Variation 32.1352093 Std Error Mean 0.1698321
Basic Statistical Measures
Location Variability
Mean 1.494802 Std Deviation 0.48036
Median 1.381944 Variance 0.23074
Mode . Range 1.27476
    Interquartile Range 0.84749
Tests for Location: Mu0=0
Test Statistic p Value
Student's t t 8.801645 Pr > |t| <.0001
Sign M 4 Pr >= |M| 0.0078
Signed Rank S 18 Pr >= |S| 0.0078
Quantiles (Definition 5)
Level Quantile
100% Max 2.268921
99% 2.268921
95% 2.268921
90% 2.268921
75% Q3 1.906608
50% Median 1.381944
25% Q1 1.059115
10% 0.994159
5% 0.994159
1% 0.994159
0% Min 0.994159
Extreme Observations
Lowest Highest
Value Obs Value Obs
0.994159 12 1.36390 7
1.022146 9 1.39999 11
1.096084 10 1.81273 13
1.363901 7 2.00049 8
1.399986 11 2.26892 6

The UNIVARIATE Procedure

Variable: mean_pancreas (% Insulin Positive Cells)

Moments
N 4 Sum Weights 4
Mean 4.81176822 Sum Observations 19.2470729
Std Deviation 2.89257447 Variance 8.36698706
Skewness 0.70986726 Kurtosis 1.64209269
Uncorrected SS 117.713415 Corrected SS 25.1009612
Coeff Variation 60.1145844 Std Error Mean 1.44628723
Basic Statistical Measures
Location Variability
Mean 4.811768 Std Deviation 2.89257
Median 4.459016 Variance 8.36699
Mode . Range 6.99679
    Interquartile Range 3.74909
Tests for Location: Mu0=0
Test Statistic p Value
Student's t t 3.32698 Pr > |t| 0.0448
Sign M 2 Pr >= |M| 0.1250
Signed Rank S 5 Pr >= |S| 0.1250
Quantiles (Definition 5)
Level Quantile
100% Max 8.66291
99% 8.66291
95% 8.66291
90% 8.66291
75% Q3 6.68631
50% Median 4.45902
25% Q1 2.93722
10% 1.66613
5% 1.66613
1% 1.66613
0% Min 1.66613
Extreme Observations
Lowest Highest
Value Obs Value Obs
1.66613 14 1.66613 14
4.20832 17 4.20832 17
4.70971 15 4.70971 15
8.66291 16 8.66291 16

The UNIVARIATE Procedure

Variable: mean_pancreas (% Insulin Positive Cells)

Moments
N 2 Sum Weights 2
Mean 1.70963311 Sum Observations 3.41926622
Std Deviation 1.02434191 Variance 1.04927635
Skewness . Kurtosis .
Uncorrected SS 6.8949671 Corrected SS 1.04927635
Coeff Variation 59.9158909 Std Error Mean 0.72431911
Basic Statistical Measures
Location Variability
Mean 1.709633 Std Deviation 1.02434
Median 1.709633 Variance 1.04928
Mode . Range 1.44864
    Interquartile Range 1.44864
Tests for Location: Mu0=0
Test Statistic p Value
Student's t t 2.360331 Pr > |t| 0.2551
Sign M 1 Pr >= |M| 0.5000
Signed Rank S 1.5 Pr >= |S| 0.5000
Quantiles (Definition 5)
Level Quantile
100% Max 2.433952
99% 2.433952
95% 2.433952
90% 2.433952
75% Q3 2.433952
50% Median 1.709633
25% Q1 0.985314
10% 0.985314
5% 0.985314
1% 0.985314
0% Min 0.985314
Extreme Observations
Lowest Highest
Value Obs Value Obs
0.985314 18 0.985314 18
2.433952 19 2.433952 19

The UNIVARIATE Procedure

Variable: mean_pancreas (% Insulin Positive Cells)

Moments
N 7 Sum Weights 7
Mean 1.49343397 Sum Observations 10.4540378
Std Deviation 0.84185486 Variance 0.7087196
Skewness 1.61052152 Kurtosis 2.7330548
Uncorrected SS 19.8647327 Corrected SS 4.25231762
Coeff Variation 56.3704105 Std Error Mean 0.31819123
Basic Statistical Measures
Location Variability
Mean 1.493434 Std Deviation 0.84185
Median 1.044920 Variance 0.70872
Mode . Range 2.47490
    Interquartile Range 0.79750
Tests for Location: Mu0=0
Test Statistic p Value
Student's t t 4.693511 Pr > |t| 0.0033
Sign M 3.5 Pr >= |M| 0.0156
Signed Rank S 14 Pr >= |S| 0.0156
Quantiles (Definition 5)
Level Quantile
100% Max 3.187238
99% 3.187238
95% 3.187238
90% 3.187238
75% Q3 1.809174
50% Median 1.044920
25% Q1 1.011670
10% 0.712339
5% 0.712339
1% 0.712339
0% Min 0.712339
Extreme Observations
Lowest Highest
Value Obs Value Obs
0.712339 23 1.03143 20
1.011670 21 1.04492 25
1.031434 20 1.65726 22
1.044920 25 1.80917 26
1.657262 22 3.18724 24

The UNIVARIATE Procedure

Variable: mean_pancreas (% Insulin Positive Cells)

Moments
N 4 Sum Weights 4
Mean 2.88266222 Sum Observations 11.5306489
Std Deviation 1.59354811 Variance 2.53939558
Skewness 1.83948625 Kurtosis 3.53172756
Uncorrected SS 40.8571527 Corrected SS 7.61818673
Coeff Variation 55.2804313 Std Error Mean 0.79677405
Basic Statistical Measures
Location Variability
Mean 2.882662 Std Deviation 1.59355
Median 2.273823 Variance 2.53940
Mode . Range 3.49979
    Interquartile Range 1.82468
Tests for Location: Mu0=0
Test Statistic p Value
Student's t t 3.617917 Pr > |t| 0.0363
Sign M 2 Pr >= |M| 0.1250
Signed Rank S 5 Pr >= |S| 0.1250
Quantiles (Definition 5)
Level Quantile
100% Max 5.24140
99% 5.24140
95% 5.24140
90% 5.24140
75% Q3 3.79500
50% Median 2.27382
25% Q1 1.97032
10% 1.74161
5% 1.74161
1% 1.74161
0% Min 1.74161
Extreme Observations
Lowest Highest
Value Obs Value Obs
1.74161 28 1.74161 28
2.19904 30 2.19904 30
2.34861 27 2.34861 27
5.24140 29 5.24140 29

The UNIVARIATE Procedure

Variable: mean_pancreas (% Insulin Positive Cells)

Moments
N 1 Sum Weights 1
Mean 2.68355667 Sum Observations 2.68355667
Std Deviation . Variance .
Skewness . Kurtosis .
Uncorrected SS 7.20147638 Corrected SS 0
Coeff Variation . Std Error Mean .
Basic Statistical Measures
Location Variability
Mean 2.683557 Std Deviation .
Median 2.683557 Variance .
Mode 2.683557 Range 0
    Interquartile Range 0
Tests for Location: Mu0=0
Test Statistic p Value
Student's t t . Pr > |t| .
Sign M 0.5 Pr >= |M| 1.0000
Signed Rank S 0.5 Pr >= |S| 1.0000
Quantiles (Definition 5)
Level Quantile
100% Max 2.68356
99% 2.68356
95% 2.68356
90% 2.68356
75% Q3 2.68356
50% Median 2.68356
25% Q1 2.68356
10% 2.68356
5% 2.68356
1% 2.68356
0% Min 2.68356
Extreme Observations
Lowest Highest
Value Obs Value Obs
2.68356 31 2.68356 31

The UNIVARIATE Procedure

Variable: mean_pancreas (% Insulin Positive Cells)

Moments
N 8 Sum Weights 8
Mean 1.4618851 Sum Observations 11.6950808
Std Deviation 0.54696355 Variance 0.29916913
Skewness 0.48553215 Kurtosis -0.1685772
Uncorrected SS 19.1910482 Corrected SS 2.0941839
Coeff Variation 37.4149483 Std Error Mean 0.19338082
Basic Statistical Measures
Location Variability
Mean 1.461885 Std Deviation 0.54696
Median 1.420192 Variance 0.29917
Mode . Range 1.64559
    Interquartile Range 0.73631
Tests for Location: Mu0=0
Test Statistic p Value
Student's t t 7.559618 Pr > |t| 0.0001
Sign M 4 Pr >= |M| 0.0078
Signed Rank S 18 Pr >= |S| 0.0078
Quantiles (Definition 5)
Level Quantile
100% Max 2.399489
99% 2.399489
95% 2.399489
90% 2.399489
75% Q3 1.793482
50% Median 1.420192
25% Q1 1.057175
10% 0.753895
5% 0.753895
1% 0.753895
0% Min 0.753895
Extreme Observations
Lowest Highest
Value Obs Value Obs
0.753895 32 1.37537 37
0.872928 39 1.46501 36
1.241422 38 1.58023 34
1.375372 37 2.00673 33
1.465013 36 2.39949 35

The UNIVARIATE Procedure

Variable: mean_pancreas (% Ki67 Positive Cells)

Moments
N 3 Sum Weights 3
Mean 3.51324356 Sum Observations 10.5397307
Std Deviation 5.61453813 Variance 31.5230384
Skewness 1.73202576 Kurtosis .
Uncorrected SS 100.074718 Corrected SS 63.0460767
Coeff Variation 159.810672 Std Error Mean 3.2415551
Basic Statistical Measures
Location Variability
Mean 3.513244 Std Deviation 5.61454
Median 0.281759 Variance 31.52304
Mode . Range 9.73472
    Interquartile Range 9.73472
Tests for Location: Mu0=0
Test Statistic p Value
Student's t t 1.083814 Pr > |t| 0.3917
Sign M 1.5 Pr >= |M| 0.2500
Signed Rank S 3 Pr >= |S| 0.2500
Quantiles (Definition 5)
Level Quantile
100% Max 9.996343
99% 9.996343
95% 9.996343
90% 9.996343
75% Q3 9.996343
50% Median 0.281759
25% Q1 0.261628
10% 0.261628
5% 0.261628
1% 0.261628
0% Min 0.261628
Extreme Observations
Lowest Highest
Value Obs Value Obs
0.261628 1 0.261628 1
0.281759 3 0.281759 3
9.996343 2 9.996343 2

The UNIVARIATE Procedure

Variable: mean_pancreas (% Ki67 Positive Cells)

Moments
N 2 Sum Weights 2
Mean 0.82301567 Sum Observations 1.64603133
Std Deviation 0.80036144 Variance 0.64057843
Skewness . Kurtosis .
Uncorrected SS 1.99528801 Corrected SS 0.64057843
Coeff Variation 97.2474122 Std Error Mean 0.565941
Basic Statistical Measures
Location Variability
Mean 0.823016 Std Deviation 0.80036
Median 0.823016 Variance 0.64058
Mode . Range 1.13188
    Interquartile Range 1.13188
Tests for Location: Mu0=0
Test Statistic p Value
Student's t t 1.454243 Pr > |t| 0.3835
Sign M 1 Pr >= |M| 0.5000
Signed Rank S 1.5 Pr >= |S| 0.5000
Quantiles (Definition 5)
Level Quantile
100% Max 1.388957
99% 1.388957
95% 1.388957
90% 1.388957
75% Q3 1.388957
50% Median 0.823016
25% Q1 0.257075
10% 0.257075
5% 0.257075
1% 0.257075
0% Min 0.257075
Extreme Observations
Lowest Highest
Value Obs Value Obs
0.257075 5 0.257075 5
1.388957 4 1.388957 4

The UNIVARIATE Procedure

Variable: mean_pancreas (% Ki67 Positive Cells)

Moments
N 8 Sum Weights 8
Mean 0.2744512 Sum Observations 2.19560957
Std Deviation 0.25882117 Variance 0.0669884
Skewness 2.67260104 Kurtosis 7.33089927
Uncorrected SS 1.07150646 Corrected SS 0.46891879
Coeff Variation 94.3049891 Std Error Mean 0.0915071
Basic Statistical Measures
Location Variability
Mean 0.274451 Std Deviation 0.25882
Median 0.191474 Variance 0.06699
Mode . Range 0.76832
    Interquartile Range 0.08979
Tests for Location: Mu0=0
Test Statistic p Value
Student's t t 2.999234 Pr > |t| 0.0200
Sign M 4 Pr >= |M| 0.0078
Signed Rank S 18 Pr >= |S| 0.0078
Quantiles (Definition 5)
Level Quantile
100% Max 0.905922
99% 0.905922
95% 0.905922
90% 0.905922
75% Q3 0.237178
50% Median 0.191474
25% Q1 0.147392
10% 0.137599
5% 0.137599
1% 0.137599
0% Min 0.137599
Extreme Observations
Lowest Highest
Value Obs Value Obs
0.137599 11 0.158978 7
0.138970 6 0.223970 13
0.155815 10 0.224060 8
0.158978 7 0.250296 12
0.223970 13 0.905922 9

The UNIVARIATE Procedure

Variable: mean_pancreas (% Ki67 Positive Cells)

Moments
N 4 Sum Weights 4
Mean 1.13409877 Sum Observations 4.53639507
Std Deviation 0.29922744 Variance 0.08953706
Skewness 1.14948692 Kurtosis 0.46411347
Uncorrected SS 5.41333123 Corrected SS 0.26861118
Coeff Variation 26.3846012 Std Error Mean 0.14961372
Basic Statistical Measures
Location Variability
Mean 1.134099 Std Deviation 0.29923
Median 1.054761 Variance 0.08954
Mode . Range 0.66145
    Interquartile Range 0.44180
Tests for Location: Mu0=0
Test Statistic p Value
Student's t t 7.580179 Pr > |t| 0.0048
Sign M 2 Pr >= |M| 0.1250
Signed Rank S 5 Pr >= |S| 0.1250
Quantiles (Definition 5)
Level Quantile
100% Max 1.544163
99% 1.544163
95% 1.544163
90% 1.544163
75% Q3 1.354997
50% Median 1.054761
25% Q1 0.913201
10% 0.882711
5% 0.882711
1% 0.882711
0% Min 0.882711
Extreme Observations
Lowest Highest
Value Obs Value Obs
0.882711 14 0.882711 14
0.943690 17 0.943690 17
1.165831 16 1.165831 16
1.544163 15 1.544163 15

The UNIVARIATE Procedure

Variable: mean_pancreas (% Ki67 Positive Cells)

Moments
N 2 Sum Weights 2
Mean 0.2189395 Sum Observations 0.437879
Std Deviation 0.01120694 Variance 0.0001256
Skewness . Kurtosis .
Uncorrected SS 0.0959946 Corrected SS 0.0001256
Coeff Variation 5.11873617 Std Error Mean 0.0079245
Basic Statistical Measures
Location Variability
Mean 0.218940 Std Deviation 0.01121
Median 0.218940 Variance 0.0001256
Mode . Range 0.01585
    Interquartile Range 0.01585
Tests for Location: Mu0=0
Test Statistic p Value
Student's t t 27.62818 Pr > |t| 0.0230
Sign M 1 Pr >= |M| 0.5000
Signed Rank S 1.5 Pr >= |S| 0.5000
Quantiles (Definition 5)
Level Quantile
100% Max 0.226864
99% 0.226864
95% 0.226864
90% 0.226864
75% Q3 0.226864
50% Median 0.218940
25% Q1 0.211015
10% 0.211015
5% 0.211015
1% 0.211015
0% Min 0.211015
Extreme Observations
Lowest Highest
Value Obs Value Obs
0.211015 19 0.211015 19
0.226864 18 0.226864 18

The UNIVARIATE Procedure

Variable: mean_pancreas (% Ki67 Positive Cells)

Moments
N 7 Sum Weights 7
Mean 0.40792956 Sum Observations 2.8555069
Std Deviation 0.44057846 Variance 0.19410938
Skewness 1.99316467 Kurtosis 4.18852102
Uncorrected SS 2.32950194 Corrected SS 1.16465627
Coeff Variation 108.003564 Std Error Mean 0.16652301
Basic Statistical Measures
Location Variability
Mean 0.407930 Std Deviation 0.44058
Median 0.176769 Variance 0.19411
Mode . Range 1.22975
    Interquartile Range 0.38146
Tests for Location: Mu0=0
Test Statistic p Value
Student's t t 2.449689 Pr > |t| 0.0498
Sign M 3.5 Pr >= |M| 0.0156
Signed Rank S 14 Pr >= |S| 0.0156
Quantiles (Definition 5)
Level Quantile
100% Max 1.339322
99% 1.339322
95% 1.339322
90% 1.339322
75% Q3 0.497986
50% Median 0.176769
25% Q1 0.116526
10% 0.109568
5% 0.109568
1% 0.109568
0% Min 0.109568
Extreme Observations
Lowest Highest
Value Obs Value Obs
0.109568 24 0.163482 20
0.116526 25 0.176769 23
0.163482 20 0.451853 22
0.176769 23 0.497986 26
0.451853 22 1.339322 21

The UNIVARIATE Procedure

Variable: mean_pancreas (% Ki67 Positive Cells)

Moments
N 4 Sum Weights 4
Mean 3.62446267 Sum Observations 14.4978507
Std Deviation 5.33721645 Variance 28.4858794
Skewness 1.89380112 Kurtosis 3.64084878
Uncorrected SS 138.004557 Corrected SS 85.4576383
Coeff Variation 147.255385 Std Error Mean 2.66860822
Basic Statistical Measures
Location Variability
Mean 3.624463 Std Deviation 5.33722
Median 1.400884 Variance 28.48588
Mode . Range 11.42033
    Interquartile Range 6.19413
Tests for Location: Mu0=0
Test Statistic p Value
Student's t t 1.358185 Pr > |t| 0.2675
Sign M 2 Pr >= |M| 0.1250
Signed Rank S 5 Pr >= |S| 0.1250
Quantiles (Definition 5)
Level Quantile
100% Max 11.558207
99% 11.558207
95% 11.558207
90% 11.558207
75% Q3 6.721530
50% Median 1.400884
25% Q1 0.527395
10% 0.137875
5% 0.137875
1% 0.137875
0% Min 0.137875
Extreme Observations
Lowest Highest
Value Obs Value Obs
0.137875 27 0.137875 27
0.916915 28 0.916915 28
1.884853 30 1.884853 30
11.558207 29 11.558207 29

The UNIVARIATE Procedure

Variable: mean_pancreas (% Ki67 Positive Cells)

Moments
N 1 Sum Weights 1
Mean 0.249871 Sum Observations 0.249871
Std Deviation . Variance .
Skewness . Kurtosis .
Uncorrected SS 0.06243552 Corrected SS 0
Coeff Variation . Std Error Mean .
Basic Statistical Measures
Location Variability
Mean 0.249871 Std Deviation .
Median 0.249871 Variance .
Mode 0.249871 Range 0
    Interquartile Range 0
Tests for Location: Mu0=0
Test Statistic p Value
Student's t t . Pr > |t| .
Sign M 0.5 Pr >= |M| 1.0000
Signed Rank S 0.5 Pr >= |S| 1.0000
Quantiles (Definition 5)
Level Quantile
100% Max 0.249871
99% 0.249871
95% 0.249871
90% 0.249871
75% Q3 0.249871
50% Median 0.249871
25% Q1 0.249871
10% 0.249871
5% 0.249871
1% 0.249871
0% Min 0.249871
Extreme Observations
Lowest Highest
Value Obs Value Obs
0.249871 31 0.249871 31

The UNIVARIATE Procedure

Variable: mean_pancreas (% Ki67 Positive Cells)

Moments
N 8 Sum Weights 8
Mean 1.39609553 Sum Observations 11.1687643
Std Deviation 1.54691886 Variance 2.39295796
Skewness 2.26341989 Kurtosis 5.79574753
Uncorrected SS 32.3433676 Corrected SS 16.7507057
Coeff Variation 110.803224 Std Error Mean 0.54691841
Basic Statistical Measures
Location Variability
Mean 1.396096 Std Deviation 1.54692
Median 1.050931 Variance 2.39296
Mode . Range 4.96172
    Interquartile Range 0.81287
Tests for Location: Mu0=0
Test Statistic p Value
Student's t t 2.552658 Pr > |t| 0.0380
Sign M 4 Pr >= |M| 0.0078
Signed Rank S 18 Pr >= |S| 0.0078
Quantiles (Definition 5)
Level Quantile
100% Max 5.0276800
99% 5.0276800
95% 5.0276800
90% 5.0276800
75% Q3 1.3997517
50% Median 1.0509310
25% Q1 0.5868772
10% 0.0659646
5% 0.0659646
1% 0.0659646
0% Min 0.0659646
Extreme Observations
Lowest Highest
Value Obs Value Obs
0.0659646 34 1.03878 32
0.2953417 38 1.06308 35
0.8784127 33 1.20636 36
1.0387837 32 1.59314 37
1.0630783 35 5.02768 39

The UNIVARIATE Procedure

Variable: mean_pancreas (% Dual Positive Cells)

Moments
N 3 Sum Weights 3
Mean 0.39920568 Sum Observations 1.19761705
Std Deviation 0.67756282 Variance 0.45909137
Skewness 1.73131036 Kurtosis .
Uncorrected SS 1.39627827 Corrected SS 0.91818274
Coeff Variation 169.727749 Std Error Mean 0.39119107
Basic Statistical Measures
Location Variability
Mean 0.399206 Std Deviation 0.67756
Median 0.014637 Variance 0.45909
Mode . Range 1.18012
    Interquartile Range 1.18012
Tests for Location: Mu0=0
Test Statistic p Value
Student's t t 1.020488 Pr > |t| 0.4148
Sign M 1.5 Pr >= |M| 0.2500
Signed Rank S 3 Pr >= |S| 0.2500
Quantiles (Definition 5)
Level Quantile
100% Max 1.18155067
99% 1.18155067
95% 1.18155067
90% 1.18155067
75% Q3 1.18155067
50% Median 0.01463737
25% Q1 0.00142901
10% 0.00142901
5% 0.00142901
1% 0.00142901
0% Min 0.00142901
Extreme Observations
Lowest Highest
Value Obs Value Obs
0.00142901 1 0.00142901 1
0.01463737 3 0.01463737 3
1.18155067 2 1.18155067 2

The UNIVARIATE Procedure

Variable: mean_pancreas (% Dual Positive Cells)

Moments
N 2 Sum Weights 2
Mean 0.00318471 Sum Observations 0.00636941
Std Deviation 0.00142242 Variance 2.02327E-6
Skewness . Kurtosis .
Uncorrected SS 0.00002231 Corrected SS 2.02327E-6
Coeff Variation 44.6640539 Std Error Mean 0.0010058
Basic Statistical Measures
Location Variability
Mean 0.003185 Std Deviation 0.00142
Median 0.003185 Variance 2.02327E-6
Mode . Range 0.00201
    Interquartile Range 0.00201
Tests for Location: Mu0=0
Test Statistic p Value
Student's t t 3.166335 Pr > |t| 0.1947
Sign M 1 Pr >= |M| 0.5000
Signed Rank S 1.5 Pr >= |S| 0.5000
Quantiles (Definition 5)
Level Quantile
100% Max 0.00419051
99% 0.00419051
95% 0.00419051
90% 0.00419051
75% Q3 0.00419051
50% Median 0.00318471
25% Q1 0.00217890
10% 0.00217890
5% 0.00217890
1% 0.00217890
0% Min 0.00217890
Extreme Observations
Lowest Highest
Value Obs Value Obs
0.00217890 5 0.00217890 5
0.00419051 4 0.00419051 4

The UNIVARIATE Procedure

Variable: mean_pancreas (% Dual Positive Cells)

Moments
N 8 Sum Weights 8
Mean 0.00543795 Sum Observations 0.04350359
Std Deviation 0.00730011 Variance 0.00005329
Skewness 1.85636345 Kurtosis 3.46469939
Uncorrected SS 0.00060961 Corrected SS 0.00037304
Coeff Variation 134.243727 Std Error Mean 0.00258098
Basic Statistical Measures
Location Variability
Mean 0.005438 Std Deviation 0.00730
Median 0.001656 Variance 0.0000533
Mode . Range 0.02115
    Interquartile Range 0.00744
Tests for Location: Mu0=0
Test Statistic p Value
Student's t t 2.106934 Pr > |t| 0.0731
Sign M 4 Pr >= |M| 0.0078
Signed Rank S 18 Pr >= |S| 0.0078
Quantiles (Definition 5)
Level Quantile
100% Max 0.021533567
99% 0.021533567
95% 0.021533567
90% 0.021533567
75% Q3 0.008290982
50% Median 0.001656097
25% Q1 0.000847823
10% 0.000380223
5% 0.000380223
1% 0.000380223
0% Min 0.000380223
Extreme Observations
Lowest Highest
Value Obs Value Obs
0.000380223 7 0.00163263 11
0.000495545 10 0.00167956 9
0.001200101 6 0.00754297 13
0.001632633 11 0.00903900 12
0.001679560 9 0.02153357 8

The UNIVARIATE Procedure

Variable: mean_pancreas (% Dual Positive Cells)

Moments
N 4 Sum Weights 4
Mean 0.02221655 Sum Observations 0.08886619
Std Deviation 0.01377753 Variance 0.00018982
Skewness 0.46780204 Kurtosis 1.15733217
Uncorrected SS 0.00254376 Corrected SS 0.00056946
Coeff Variation 62.0147385 Std Error Mean 0.00688877
Basic Statistical Measures
Location Variability
Mean 0.022217 Std Deviation 0.01378
Median 0.021096 Variance 0.0001898
Mode . Range 0.03332
    Interquartile Range 0.01881
Tests for Location: Mu0=0
Test Statistic p Value
Student's t t 3.22504 Pr > |t| 0.0484
Sign M 2 Pr >= |M| 0.1250
Signed Rank S 5 Pr >= |S| 0.1250
Quantiles (Definition 5)
Level Quantile
100% Max 0.03999863
99% 0.03999863
95% 0.03999863
90% 0.03999863
75% Q3 0.03162050
50% Median 0.02109623
25% Q1 0.01281260
10% 0.00667509
5% 0.00667509
1% 0.00667509
0% Min 0.00667509
Extreme Observations
Lowest Highest
Value Obs Value Obs
0.00667509 14 0.00667509 14
0.01895010 17 0.01895010 17
0.02324237 15 0.02324237 15
0.03999863 16 0.03999863 16

The UNIVARIATE Procedure

Variable: mean_pancreas (% Dual Positive Cells)

Moments
N 2 Sum Weights 2
Mean 0.0286594 Sum Observations 0.0573188
Std Deviation 0.02370613 Variance 0.00056198
Skewness . Kurtosis .
Uncorrected SS 0.0022047 Corrected SS 0.00056198
Coeff Variation 82.7167899 Std Error Mean 0.01676277
Basic Statistical Measures
Location Variability
Mean 0.028659 Std Deviation 0.02371
Median 0.028659 Variance 0.0005620
Mode . Range 0.03353
    Interquartile Range 0.03353
Tests for Location: Mu0=0
Test Statistic p Value
Student's t t 1.709706 Pr > |t| 0.3369
Sign M 1 Pr >= |M| 0.5000
Signed Rank S 1.5 Pr >= |S| 0.5000
Quantiles (Definition 5)
Level Quantile
100% Max 0.0454222
99% 0.0454222
95% 0.0454222
90% 0.0454222
75% Q3 0.0454222
50% Median 0.0286594
25% Q1 0.0118966
10% 0.0118966
5% 0.0118966
1% 0.0118966
0% Min 0.0118966
Extreme Observations
Lowest Highest
Value Obs Value Obs
0.0118966 18 0.0118966 18
0.0454222 19 0.0454222 19

The UNIVARIATE Procedure

Variable: mean_pancreas (% Dual Positive Cells)

Moments
N 7 Sum Weights 7
Mean 0.00463112 Sum Observations 0.03241785
Std Deviation 0.00482119 Variance 0.00002324
Skewness 2.09090487 Kurtosis 4.48332376
Uncorrected SS 0.00028959 Corrected SS 0.00013946
Coeff Variation 104.104192 Std Error Mean 0.00182224
Basic Statistical Measures
Location Variability
Mean 0.004631 Std Deviation 0.00482
Median 0.002531 Variance 0.0000232
Mode . Range 0.01355
    Interquartile Range 0.00457
Tests for Location: Mu0=0
Test Statistic p Value
Student's t t 2.541446 Pr > |t| 0.0440
Sign M 3.5 Pr >= |M| 0.0156
Signed Rank S 14 Pr >= |S| 0.0156
Quantiles (Definition 5)
Level Quantile
100% Max 0.01491478
99% 0.01491478
95% 0.01491478
90% 0.01491478
75% Q3 0.00620572
50% Median 0.00253109
25% Q1 0.00163843
10% 0.00136837
5% 0.00136837
1% 0.00136837
0% Min 0.00136837
Extreme Observations
Lowest Highest
Value Obs Value Obs
0.00136837 25 0.00214361 22
0.00163843 23 0.00253109 24
0.00214361 22 0.00361584 20
0.00253109 24 0.00620572 21
0.00361584 20 0.01491478 26

The UNIVARIATE Procedure

Variable: mean_pancreas (% Dual Positive Cells)

Moments
N 4 Sum Weights 4
Mean 0.06609016 Sum Observations 0.26436065
Std Deviation 0.11519892 Variance 0.01327079
Skewness 1.97792543 Kurtosis 3.92416239
Uncorrected SS 0.05728401 Corrected SS 0.03981237
Coeff Variation 174.305692 Std Error Mean 0.05759946
Basic Statistical Measures
Location Variability
Mean 0.066090 Std Deviation 0.11520
Median 0.012322 Variance 0.01327
Mode . Range 0.23742
    Interquartile Range 0.12439
Tests for Location: Mu0=0
Test Statistic p Value
Student's t t 1.147409 Pr > |t| 0.3344
Sign M 2 Pr >= |M| 0.1250
Signed Rank S 5 Pr >= |S| 0.1250
Quantiles (Definition 5)
Level Quantile
100% Max 0.23856733
99% 0.23856733
95% 0.23856733
90% 0.23856733
75% Q3 0.12828733
50% Median 0.01232233
25% Q1 0.00389299
10% 0.00114866
5% 0.00114866
1% 0.00114866
0% Min 0.00114866
Extreme Observations
Lowest Highest
Value Obs Value Obs
0.00114866 27 0.00114866 27
0.00663733 30 0.00663733 30
0.01800733 28 0.01800733 28
0.23856733 29 0.23856733 29

The UNIVARIATE Procedure

Variable: mean_pancreas (% Dual Positive Cells)

Moments
N 1 Sum Weights 1
Mean 0.00277371 Sum Observations 0.00277371
Std Deviation . Variance .
Skewness . Kurtosis .
Uncorrected SS 7.69345E-6 Corrected SS 0
Coeff Variation . Std Error Mean .
Basic Statistical Measures
Location Variability
Mean 0.002774 Std Deviation .
Median 0.002774 Variance .
Mode 0.002774 Range 0
    Interquartile Range 0
Tests for Location: Mu0=0
Test Statistic p Value
Student's t t . Pr > |t| .
Sign M 0.5 Pr >= |M| 1.0000
Signed Rank S 0.5 Pr >= |S| 1.0000
Quantiles (Definition 5)
Level Quantile
100% Max 0.00277371
99% 0.00277371
95% 0.00277371
90% 0.00277371
75% Q3 0.00277371
50% Median 0.00277371
25% Q1 0.00277371
10% 0.00277371
5% 0.00277371
1% 0.00277371
0% Min 0.00277371
Extreme Observations
Lowest Highest
Value Obs Value Obs
0.00277371 31 0.00277371 31

The UNIVARIATE Procedure

Variable: mean_pancreas (% Dual Positive Cells)

Moments
N 8 Sum Weights 8
Mean 0.00844121 Sum Observations 0.06752969
Std Deviation 0.00860456 Variance 0.00007404
Skewness 1.00206165 Kurtosis -0.2898604
Uncorrected SS 0.0010883 Corrected SS 0.00051827
Coeff Variation 101.935095 Std Error Mean 0.00304217
Basic Statistical Measures
Location Variability
Mean 0.008441 Std Deviation 0.00860
Median 0.004063 Variance 0.0000740
Mode . Range 0.02376
    Interquartile Range 0.01282
Tests for Location: Mu0=0
Test Statistic p Value
Student's t t 2.774733 Pr > |t| 0.0275
Sign M 4 Pr >= |M| 0.0078
Signed Rank S 18 Pr >= |S| 0.0078
Quantiles (Definition 5)
Level Quantile
100% Max 0.024161200
99% 0.024161200
95% 0.024161200
90% 0.024161200
75% Q3 0.015118298
50% Median 0.004062707
25% Q1 0.002300953
10% 0.000404572
5% 0.000404572
1% 0.000404572
0% Min 0.000404572
Extreme Observations
Lowest Highest
Value Obs Value Obs
0.000404572 32 0.00387639 34
0.001499636 38 0.00424903 33
0.003102270 37 0.01404723 36
0.003876387 34 0.01618937 39
0.004249027 33 0.02416120 35

Obs hospbin age_group mean_pancreas_group dataset
1 3 1 3.72530 CD45
2 3 2 6.05577 CD45
3 3 3 3.76406 CD45
4 6 1 4.64097 CD45
5 6 2 1.87041 CD45
6 6 3 6.01346 CD45
7 9 1 5.06362 CD45
8 9 2 3.60926 CD45
9 9 3 6.47411 CD45
10 3 1 1.71938 CD68
11 3 2 4.50595 CD68
12 3 3 1.53061 CD68
13 6 1 2.97855 CD68
14 6 2 1.15444 CD68
15 6 3 2.98796 CD68
16 9 1 4.73337 CD68
17 9 2 1.44925 CD68
18 9 3 4.25196 CD68
19 3 1 7.02597 Insulin(I)
20 3 2 1.67156 Insulin(I)
21 3 3 1.49480 Insulin(I)
22 6 1 4.81177 Insulin(I)
23 6 2 1.70963 Insulin(I)
24 6 3 1.49343 Insulin(I)
25 9 1 2.88266 Insulin(I)
26 9 2 2.68356 Insulin(I)
27 9 3 1.46189 Insulin(I)
28 3 1 3.51324 Ki67
29 3 2 0.82302 Ki67
30 3 3 0.27445 Ki67
31 6 1 1.13410 Ki67
32 6 2 0.21894 Ki67
33 6 3 0.40793 Ki67
34 9 1 3.62446 Ki67
35 9 2 0.24987 Ki67
36 9 3 1.39610 Ki67
37 3 1 0.39921 Ki67+I
38 3 2 0.00318 Ki67+I
39 3 3 0.00544 Ki67+I
40 6 1 0.02222 Ki67+I
41 6 2 0.02866 Ki67+I
42 6 3 0.00463 Ki67+I
43 9 1 0.06609 Ki67+I
44 9 2 0.00277 Ki67+I
45 9 3 0.00844 Ki67+I

The SGPanel Procedure

Reviewer asked about the differences between insulin and CD45 and asked for a comparison; thus the analysis below. However, the results were not included in the manuscript. Since none of these CD45+ cells were observed to be in direct proximity to insulin positive cells, this comparison is difficult to interpret without additional data to determine if these CD45+ cells are resident or trafficking cells.

In [50]:
/*to prepare the data for visualization and analysis*/

DATA cd45_temp (keep = case sample_type2 Positive_cells_percentage stain);
     set cd45;
     Stain="CD45    ";
     rename percent_cd45=Positive_cells_percentage;
run;

DATA insulin_temp (keep = case sample_type2 Positive_cells_percentage stain);
     set cd45;
     Stain="Insulin";
     rename percent_insulin=Positive_cells_percentage;
run;


DATA cd45_insulin;
     set cd45_temp insulin_temp;
     Rename sample_type2=Region;
run;

PROC export data=cd45_insulin 
     outfile="cd45_insulin.csv" 
     dbms=csv
     replace;
run; 

/*to obtain all LSmeans and SE values, perform individual comparisons, retrieve differences and assoc. confidence intervals*/
PROC mixed data=cd45_insulin;
class case stain region;
model positive_cells_percentage=stain|region;
repeated stain/subject=case(region) type=un;
lsmeans region|stain / adjust=tukey cl pdiff alpha=0.05;
run;
Out[50]:
SAS Output

The Mixed Procedure

Model Information
Data Set WORK.CD45_INSULIN
Dependent Variable Positive_cells_percentage
Covariance Structure Unstructured
Subject Effect Case(Region)
Estimation Method REML
Residual Variance Method None
Fixed Effects SE Method Model-Based
Degrees of Freedom Method Between-Within
Class Level Information
Class Levels Values
Case 39 6003 6005 6007 6008 6011 6019 6047 6048 6057 6060 6073 6099 6104 6106 6115 6117 6126 6129 6131 6134 6140 6144 6162 6165 6172 6174 6178 6179 6187 6200 6219 6229 6230 6235 6250 6251 6254 6278 6279
Stain 2 CD45 Insulin
Region 3 A B C
Dimensions
Covariance Parameters 3
Columns in X 12
Columns in Z 0
Subjects 117
Max Obs per Subject 2
Number of Observations
Number of Observations Read 234
Number of Observations Used 234
Number of Observations Not Used 0
Iteration History
Iteration Evaluations -2 Res Log Like Criterion
0 1 1232.73169244  
1 1 1231.36667260 0.00000000
Convergence criteria met.
Covariance Parameter Estimates
Cov Parm Subject Estimate
UN(1,1) Case(Region) 13.1441
UN(2,1) Case(Region) -0.01656
UN(2,2) Case(Region) 10.5584
Fit Statistics
-2 Res Log Likelihood 1231.4
AIC (Smaller is Better) 1237.4
AICC (Smaller is Better) 1237.5
BIC (Smaller is Better) 1245.7
Null Model Likelihood Ratio Test
DF Chi-Square Pr > ChiSq
2 1.37 0.5053
Type 3 Tests of Fixed Effects
Effect Num DF Den DF F Value Pr > F
Stain 1 114 24.52 <.0001
Region 2 114 1.51 0.2246
Stain*Region 2 114 0.23 0.7943
Least Squares Means
Effect Stain Region Estimate Standard
Error
DF t Value Pr > |t| Alpha Lower Upper
Region   A 3.5015 0.3895 114 8.99 <.0001 0.05 2.7299 4.2732
Region   B 3.6415 0.3895 114 9.35 <.0001 0.05 2.8698 4.4131
Region   C 4.3925 0.3895 114 11.28 <.0001 0.05 3.6209 5.1642
Stain CD45   4.9604 0.3352 114 14.80 <.0001 0.05 4.2964 5.6244
Stain Insulin   2.7300 0.3004 114 9.09 <.0001 0.05 2.1349 3.3251
Stain*Region CD45 A 4.4040 0.5805 114 7.59 <.0001 0.05 3.2540 5.5541
Stain*Region CD45 B 4.8286 0.5805 114 8.32 <.0001 0.05 3.6786 5.9786
Stain*Region CD45 C 5.6485 0.5805 114 9.73 <.0001 0.05 4.4985 6.7986
Stain*Region Insulin A 2.5990 0.5203 114 5.00 <.0001 0.05 1.5683 3.6297
Stain*Region Insulin B 2.4544 0.5203 114 4.72 <.0001 0.05 1.4236 3.4851
Stain*Region Insulin C 3.1365 0.5203 114 6.03 <.0001 0.05 2.1058 4.1673
Differences of Least Squares Means
Effect Stain Region _Stain _Region Estimate Standard
Error
DF t Value Pr > |t| Adjustment Adj P Alpha Lower Upper Adj Lower Adj Upper
Region   A   B -0.1400 0.5509 114 -0.25 0.7999 Tukey 0.9651 0.05 -1.2312 0.9513 -1.4481 1.1682
Region   A   C -0.8910 0.5509 114 -1.62 0.1085 Tukey 0.2424 0.05 -1.9823 0.2003 -2.1992 0.4171
Region   B   C -0.7511 0.5509 114 -1.36 0.1754 Tukey 0.3635 0.05 -1.8423 0.3402 -2.0592 0.5571
Stain CD45   Insulin   2.2304 0.4504 114 4.95 <.0001 Tukey-Kramer <.0001 0.05 1.3382 3.1227 1.3382 3.1227
Stain*Region CD45 A CD45 B -0.4246 0.8210 114 -0.52 0.6061 Tukey-Kramer 0.9954 0.05 -2.0510 1.2019 -2.8045 1.9554
Stain*Region CD45 A CD45 C -1.2445 0.8210 114 -1.52 0.1323 Tukey-Kramer 0.6549 0.05 -2.8709 0.3819 -3.6244 1.1354
Stain*Region CD45 A Insulin A 1.8050 0.7801 114 2.31 0.0225 Tukey-Kramer 0.1971 0.05 0.2596 3.3505 -0.4564 4.0665
Stain*Region CD45 A Insulin B 1.9497 0.7796 114 2.50 0.0138 Tukey-Kramer 0.1325 0.05 0.4053 3.4940 -0.3102 4.2095
Stain*Region CD45 A Insulin C 1.2675 0.7796 114 1.63 0.1067 Tukey-Kramer 0.5833 0.05 -0.2768 2.8119 -0.9923 3.5274
Stain*Region CD45 B CD45 C -0.8200 0.8210 114 -1.00 0.3200 Tukey-Kramer 0.9175 0.05 -2.4464 0.8065 -3.1999 1.5600
Stain*Region CD45 B Insulin A 2.2296 0.7796 114 2.86 0.0050 Tukey-Kramer 0.0554 0.05 0.6852 3.7739 -0.03026 4.4894
Stain*Region CD45 B Insulin B 2.3742 0.7801 114 3.04 0.0029 Tukey-Kramer 0.0337 0.05 0.8288 3.9197 0.1128 4.6357
Stain*Region CD45 B Insulin C 1.6921 0.7796 114 2.17 0.0320 Tukey-Kramer 0.2597 0.05 0.1477 3.2364 -0.5678 3.9519
Stain*Region CD45 C Insulin A 3.0495 0.7796 114 3.91 0.0002 Tukey-Kramer 0.0021 0.05 1.5052 4.5939 0.7897 5.3094
Stain*Region CD45 C Insulin B 3.1942 0.7796 114 4.10 <.0001 Tukey-Kramer 0.0011 0.05 1.6498 4.7385 0.9343 5.4540
Stain*Region CD45 C Insulin C 2.5120 0.7801 114 3.22 0.0017 Tukey-Kramer 0.0202 0.05 0.9666 4.0575 0.2506 4.7735
Stain*Region Insulin A Insulin B 0.1447 0.7358 114 0.20 0.8445 Tukey-Kramer 1.0000 0.05 -1.3130 1.6023 -1.9884 2.2777
Stain*Region Insulin A Insulin C -0.5375 0.7358 114 -0.73 0.4666 Tukey-Kramer 0.9778 0.05 -1.9952 0.9202 -2.6705 1.5955
Stain*Region Insulin B Insulin C -0.6822 0.7358 114 -0.93 0.3559 Tukey-Kramer 0.9388 0.05 -2.1399 0.7755 -2.8152 1.4509