* Verallgemeinerte Schätzungsgleichungen. GENLIN response (REFERENCE=FIRST) BY group stimulation condition delay_frames (ORDER=ASCENDING)   /MODEL group stimulation condition delay_frames group*stimulation group*condition     group*delay_frames stimulation*condition stimulation*delay_frames condition*delay_frames     group*stimulation*condition group*stimulation*delay_frames group*condition*delay_frames     stimulation*condition*delay_frames group*stimulation*condition*delay_frames INTERCEPT=YES  DISTRIBUTION=BINOMIAL LINK=LOGIT   /CRITERIA METHOD=FISHER(1) SCALE=1 MAXITERATIONS=100 MAXSTEPHALVING=5 PCONVERGE=1E-006(ABSOLUTE)     SINGULAR=1E-012 ANALYSISTYPE=3(WALD) CILEVEL=95 LIKELIHOOD=FULL   /EMMEANS TABLES=group*stimulation*condition*delay_frames SCALE=ORIGINAL     COMPARE=group*stimulation*condition*delay_frames CONTRAST=PAIRWISE PADJUST=LSD   /EMMEANS TABLES=group*stimulation*delay_frames SCALE=ORIGINAL     COMPARE=group*stimulation*delay_frames CONTRAST=PAIRWISE PADJUST=LSD   /EMMEANS TABLES=group*delay_frames SCALE=ORIGINAL COMPARE=group*delay_frames CONTRAST=PAIRWISE     PADJUST=LSD   /REPEATED SUBJECT=id SORT=YES CORRTYPE=AR(1) ADJUSTCORR=YES COVB=ROBUST MAXITERATIONS=100     PCONVERGE=1e-006(ABSOLUTE) UPDATECORR=1   /MISSING CLASSMISSING=EXCLUDE   /PRINT CPS DESCRIPTIVES MODELINFO FIT SUMMARY SOLUTION.


Verallgemeinerte lineare Modelle


Anmerkungen
Ausgabe erstellt 31-Jul-2020 15:41:26
Kommentare
Eingabe Daten E:\GoogleDrive\2_Causality\tDCS\Manuscripts\04_ButtonPress_Patients\03_tDCS_SZ\04_Brain_Communications\GEE_bp_ssd_hc_BrainCommunications_final.sav
Aktiver Datensatz DatenSet1
Filter <keine>
Gewichtung <keine>
Aufgeteilte Datei <keine>
Anzahl der Zeilen in der Arbeitsdatei 21600
Behandlung fehlender Werte Definition für "fehlend" Benutzerdefiniert fehlende Werte für Faktor-, Subjekt- und Innersubjektvariablen werden als fehlend behandelt.
Verwendete Fälle Die Statistiken beruhen auf Fällen mit gültigen Daten für alle Variablen im Modell.
Umgang mit Gewichten nicht zutreffend
Syntax GENLIN response (REFERENCE=FIRST) BY group stimulation condition delay_frames (ORDER=ASCENDING)
/MODEL group stimulation condition delay_frames group*stimulation group*condition
group*delay_frames stimulation*condition stimulation*delay_frames condition*delay_frames
group*stimulation*condition group*stimulation*delay_frames group*condition*delay_frames
stimulation*condition*delay_frames group*stimulation*condition*delay_frames INTERCEPT=YES
DISTRIBUTION=BINOMIAL LINK=LOGIT
/CRITERIA METHOD=FISHER(1) SCALE=1 MAXITERATIONS=100 MAXSTEPHALVING=5 PCONVERGE=1E-006(ABSOLUTE)
SINGULAR=1E-012 ANALYSISTYPE=3(WALD) CILEVEL=95 LIKELIHOOD=FULL
/EMMEANS TABLES=group*stimulation*condition*delay_frames SCALE=ORIGINAL
COMPARE=group*stimulation*condition*delay_frames CONTRAST=PAIRWISE PADJUST=LSD
/EMMEANS TABLES=group*stimulation*delay_frames SCALE=ORIGINAL
COMPARE=group*stimulation*delay_frames CONTRAST=PAIRWISE PADJUST=LSD
/EMMEANS TABLES=group*delay_frames SCALE=ORIGINAL COMPARE=group*delay_frames CONTRAST=PAIRWISE
PADJUST=LSD
/REPEATED SUBJECT=id SORT=YES CORRTYPE=AR(1) ADJUSTCORR=YES COVB=ROBUST MAXITERATIONS=100
PCONVERGE=1e-006(ABSOLUTE) UPDATECORR=1
/MISSING CLASSMISSING=EXCLUDE
/PRINT CPS DESCRIPTIVES MODELINFO FIT SUMMARY SOLUTION.
Ressourcen Prozessorzeit 00:04:00.109
Verstrichene Zeit 00:04:06.578


[DatenSet1] E:\GoogleDrive\2_Causality\tDCS\Manuscripts\04_ButtonPress_Patients\03_tDCS_SZ\04_Brain_Communications\GEE_bp_ssd_hc_BrainCommunications_final.sav
Modellinformationen
Abhängige Variable responsea
Wahrscheinlichkeitsverteilung Binomial
Verknüpfungsfunktion Logit
Subjekteffekt 1 id
Struktur der Arbeitskorrelationsmatrix AR(1)
a. Die Prozedur modelliert delay als Antwort und behandelt no-delay dabei als Referenzkategorie.

Zusammenfassung der Fallverarbeitung
  N Prozent
Eingeschlossen 21351 98.8%
Ausgeschlossen 249 1.2%
Gesamt 21600 100.0%

Korrelierte Datenzusammenfassung
Anzahl der Niveaus Subjekteffekt id 45
Anzahl der Subjekte 45
Anzahl der Messungen pro Subjekt Minimum 408
Maximum 480
Dimension der Korrelationsmatrix 480

Informationen zu kategorialen Variablen
  N Prozent
Abhängige Variable response no-delay 11535 54.0%
delay 9816 46.0%
Gesamt 21351 100.0%
Faktor group HC 12362 57.9%
SSD 8989 42.1%
Gesamt 21351 100.0%
stimulation LFC-RFA 5359 25.1%
LPC-RPA 5312 24.9%
LFC-RPA 5345 25.0%
sham 5335 25.0%
Gesamt 21351 100.0%
condition active 10717 50.2%
passive 10634 49.8%
Gesamt 21351 100.0%
delay_frames .00 3571 16.7%
5.00 3565 16.7%
10.00 3556 16.7%
15.00 3563 16.7%
20.00 3554 16.6%
25.00 3542 16.6%
Gesamt 21351 100.0%

Anpassungsgüteb
  Wert
Quasi-Likelihood unter Unabhängigkeitsmodellkriterium (QIC)a 23644.673
Korrigierte Quasi-Likelihood unter Unabhängigkeitsmodellkriterium (QICC)a 23198.726
Abhängige Variable: response
Modell: (Konstanter Term), group, stimulation, condition, delay_frames, group * stimulation, group * condition, group * delay_frames, stimulation * condition, stimulation * delay_frames, condition * delay_frames, group * stimulation * condition, group * stimulation * delay_frames, group * condition * delay_frames, stimulation * condition * delay_frames, group * stimulation * condition * delay_frames
a. Mithilfe der vollständigen Log-Quasi-Likelihood-Funktion berechnet.
b. Die Informationskriterien liegen in einem möglichst kleinem Format vor.

Tests der Modelleffekte
Quelle Typ III
Wald-Chi-Quadrat df Sig.
(Konstanter Term) 4.850 1 .028
group 9.175 1 .002
stimulation 5.497 3 .139
condition 1.637 1 .201
delay_frames 166.629 5 .000
group * stimulation 7.945 3 .047
group * condition 1.642 1 .200
group * delay_frames 11.731 5 .039
stimulation * condition 2.268 3 .519
stimulation * delay_frames 38.580 15 .001
condition * delay_frames 26.164 5 .000
group * stimulation * condition .592 3 .898
group * stimulation * delay_frames 84.570 15 .000
group * condition * delay_frames 3.456 5 .630
stimulation * condition * delay_frames 77.926 15 .000
group * stimulation * condition * delay_frames 42.443 15 .000
Abhängige Variable: response
Modell: (Konstanter Term), group, stimulation, condition, delay_frames, group * stimulation, group * condition, group * delay_frames, stimulation * condition, stimulation * delay_frames, condition * delay_frames, group * stimulation * condition, group * stimulation * delay_frames, group * condition * delay_frames, stimulation * condition * delay_frames, group * stimulation * condition * delay_frames

Parameterschätzer
Parameter RegressionskoeffizientB Standardfehler 95% Wald-Konfidenzintervall Hypothesentest
Unterer Wert Oberer Wert Wald-Chi-Quadrat df Sig.
(Konstanter Term) .549 .3385 -.114 1.212 2.630 1 .105
[group=.00] 1.376 .4512 .492 2.261 9.303 1 .002
[group=1.00] 0a . . . . . .
[stimulation=1.00] .057 .1871 -.309 .424 .094 1 .759
[stimulation=3.00] -.148 .1669 -.475 .179 .785 1 .376
[stimulation=5.00] .392 .2290 -.057 .840 2.924 1 .087
[stimulation=7.00] 0a . . . . . .
[condition=1.00] .084 .1993 -.307 .474 .176 1 .675
[condition=2.00] 0a . . . . . .
[delay_frames=.00] -2.094 .5159 -3.105 -1.083 16.479 1 .000
[delay_frames=5.00] -2.462 .4594 -3.362 -1.561 28.716 1 .000
[delay_frames=10.00] -1.531 .3529 -2.223 -.839 18.824 1 .000
[delay_frames=15.00] -.798 .2237 -1.237 -.360 12.733 1 .000
[delay_frames=20.00] -.360 .2387 -.827 .108 2.269 1 .132
[delay_frames=25.00] 0a . . . . . .
[group=.00] * [stimulation=1.00] -.451 .2704 -.981 .079 2.779 1 .095
[group=.00] * [stimulation=3.00] -.106 .3363 -.765 .553 .099 1 .753
[group=.00] * [stimulation=5.00] -.547 .3218 -1.178 .083 2.894 1 .089
[group=.00] * [stimulation=7.00] 0a . . . . . .
[group=1.00] * [stimulation=1.00] 0a . . . . . .
[group=1.00] * [stimulation=3.00] 0a . . . . . .
[group=1.00] * [stimulation=5.00] 0a . . . . . .
[group=1.00] * [stimulation=7.00] 0a . . . . . .
[group=.00] * [condition=1.00] .026 .3847 -.728 .780 .005 1 .946
[group=.00] * [condition=2.00] 0a . . . . . .
[group=1.00] * [condition=1.00] 0a . . . . . .
[group=1.00] * [condition=2.00] 0a . . . . . .
[group=.00] * [delay_frames=.00] -2.154 .6911 -3.509 -.800 9.716 1 .002
[group=.00] * [delay_frames=5.00] -1.049 .6188 -2.261 .164 2.872 1 .090
[group=.00] * [delay_frames=10.00] -.792 .4815 -1.735 .152 2.704 1 .100
[group=.00] * [delay_frames=15.00] -.709 .3607 -1.416 -.002 3.859 1 .049
[group=.00] * [delay_frames=20.00] -.171 .3564 -.870 .527 .230 1 .631
[group=.00] * [delay_frames=25.00] 0a . . . . . .
[group=1.00] * [delay_frames=.00] 0a . . . . . .
[group=1.00] * [delay_frames=5.00] 0a . . . . . .
[group=1.00] * [delay_frames=10.00] 0a . . . . . .
[group=1.00] * [delay_frames=15.00] 0a . . . . . .
[group=1.00] * [delay_frames=20.00] 0a . . . . . .
[group=1.00] * [delay_frames=25.00] 0a . . . . . .
[stimulation=1.00] * [condition=1.00] .366 .1998 -.026 .757 3.347 1 .067
[stimulation=1.00] * [condition=2.00] 0a . . . . . .
[stimulation=3.00] * [condition=1.00] .582 .3310 -.067 1.231 3.087 1 .079
[stimulation=3.00] * [condition=2.00] 0a . . . . . .
[stimulation=5.00] * [condition=1.00] .148 .2670 -.375 .671 .307 1 .580
[stimulation=5.00] * [condition=2.00] 0a . . . . . .
[stimulation=7.00] * [condition=1.00] 0a . . . . . .
[stimulation=7.00] * [condition=2.00] 0a . . . . . .
[stimulation=1.00] * [delay_frames=.00] -.990 .4280 -1.829 -.151 5.350 1 .021
[stimulation=1.00] * [delay_frames=5.00] -.411 .4154 -1.225 .403 .980 1 .322
[stimulation=1.00] * [delay_frames=10.00] -.100 .3401 -.766 .567 .086 1 .769
[stimulation=1.00] * [delay_frames=15.00] -.195 .2237 -.634 .243 .761 1 .383
[stimulation=1.00] * [delay_frames=20.00] .200 .2753 -.340 .739 .526 1 .468
[stimulation=1.00] * [delay_frames=25.00] 0a . . . . . .
[stimulation=3.00] * [delay_frames=.00] -.575 .3347 -1.231 .081 2.950 1 .086
[stimulation=3.00] * [delay_frames=5.00] .184 .2267 -.260 .628 .658 1 .417
[stimulation=3.00] * [delay_frames=10.00] .133 .3526 -.558 .824 .142 1 .706
[stimulation=3.00] * [delay_frames=15.00] .015 .1549 -.289 .318 .009 1 .925
[stimulation=3.00] * [delay_frames=20.00] .260 .2692 -.268 .787 .930 1 .335
[stimulation=3.00] * [delay_frames=25.00] 0a . . . . . .
[stimulation=5.00] * [delay_frames=.00] -.675 .3919 -1.443 .093 2.964 1 .085
[stimulation=5.00] * [delay_frames=5.00] -.355 .5226 -1.379 .670 .461 1 .497
[stimulation=5.00] * [delay_frames=10.00] -.120 .4150 -.934 .693 .084 1 .772
[stimulation=5.00] * [delay_frames=15.00] -.164 .2492 -.653 .324 .434 1 .510
[stimulation=5.00] * [delay_frames=20.00] -.392 .2902 -.960 .177 1.822 1 .177
[stimulation=5.00] * [delay_frames=25.00] 0a . . . . . .
[stimulation=7.00] * [delay_frames=.00] 0a . . . . . .
[stimulation=7.00] * [delay_frames=5.00] 0a . . . . . .
[stimulation=7.00] * [delay_frames=10.00] 0a . . . . . .
[stimulation=7.00] * [delay_frames=15.00] 0a . . . . . .
[stimulation=7.00] * [delay_frames=20.00] 0a . . . . . .
[stimulation=7.00] * [delay_frames=25.00] 0a . . . . . .
[condition=1.00] * [delay_frames=.00] -1.163 .2895 -1.730 -.595 16.129 1 .000
[condition=1.00] * [delay_frames=5.00] -.186 .2694 -.714 .342 .479 1 .489
[condition=1.00] * [delay_frames=10.00] -.039 .3783 -.780 .703 .011 1 .918
[condition=1.00] * [delay_frames=15.00] .323 .2744 -.215 .861 1.383 1 .240
[condition=1.00] * [delay_frames=20.00] .248 .2895 -.319 .816 .735 1 .391
[condition=1.00] * [delay_frames=25.00] 0a . . . . . .
[condition=2.00] * [delay_frames=.00] 0a . . . . . .
[condition=2.00] * [delay_frames=5.00] 0a . . . . . .
[condition=2.00] * [delay_frames=10.00] 0a . . . . . .
[condition=2.00] * [delay_frames=15.00] 0a . . . . . .
[condition=2.00] * [delay_frames=20.00] 0a . . . . . .
[condition=2.00] * [delay_frames=25.00] 0a . . . . . .
[group=.00] * [stimulation=1.00] * [condition=1.00] -.017 .3770 -.756 .722 .002 1 .964
[group=.00] * [stimulation=1.00] * [condition=2.00] 0a . . . . . .
[group=.00] * [stimulation=3.00] * [condition=1.00] -.224 .5108 -1.225 .777 .192 1 .661
[group=.00] * [stimulation=3.00] * [condition=2.00] 0a . . . . . .
[group=.00] * [stimulation=5.00] * [condition=1.00] -.257 .4373 -1.114 .600 .346 1 .556
[group=.00] * [stimulation=5.00] * [condition=2.00] 0a . . . . . .
[group=.00] * [stimulation=7.00] * [condition=1.00] 0a . . . . . .
[group=.00] * [stimulation=7.00] * [condition=2.00] 0a . . . . . .
[group=1.00] * [stimulation=1.00] * [condition=1.00] 0a . . . . . .
[group=1.00] * [stimulation=1.00] * [condition=2.00] 0a . . . . . .
[group=1.00] * [stimulation=3.00] * [condition=1.00] 0a . . . . . .
[group=1.00] * [stimulation=3.00] * [condition=2.00] 0a . . . . . .
[group=1.00] * [stimulation=5.00] * [condition=1.00] 0a . . . . . .
[group=1.00] * [stimulation=5.00] * [condition=2.00] 0a . . . . . .
[group=1.00] * [stimulation=7.00] * [condition=1.00] 0a . . . . . .
[group=1.00] * [stimulation=7.00] * [condition=2.00] 0a . . . . . .
[group=.00] * [stimulation=1.00] * [delay_frames=.00] 2.166 .5262 1.134 3.197 16.942 1 .000
[group=.00] * [stimulation=1.00] * [delay_frames=5.00] 1.034 .5444 -.033 2.101 3.604 1 .058
[group=.00] * [stimulation=1.00] * [delay_frames=10.00] .624 .4633 -.284 1.532 1.814 1 .178
[group=.00] * [stimulation=1.00] * [delay_frames=15.00] .699 .3518 .009 1.388 3.943 1 .047
[group=.00] * [stimulation=1.00] * [delay_frames=20.00] -.138 .3879 -.898 .622 .127 1 .722
[group=.00] * [stimulation=1.00] * [delay_frames=25.00] 0a . . . . . .
[group=.00] * [stimulation=3.00] * [delay_frames=.00] 1.534 .5391 .478 2.591 8.100 1 .004
[group=.00] * [stimulation=3.00] * [delay_frames=5.00] .681 .4696 -.239 1.602 2.105 1 .147
[group=.00] * [stimulation=3.00] * [delay_frames=10.00] .331 .4963 -.642 1.304 .445 1 .505
[group=.00] * [stimulation=3.00] * [delay_frames=15.00] .344 .3991 -.438 1.126 .742 1 .389
[group=.00] * [stimulation=3.00] * [delay_frames=20.00] -.460 .4952 -1.431 .510 .864 1 .353
[group=.00] * [stimulation=3.00] * [delay_frames=25.00] 0a . . . . . .
[group=.00] * [stimulation=5.00] * [delay_frames=.00] 1.846 .6014 .667 3.024 9.420 1 .002
[group=.00] * [stimulation=5.00] * [delay_frames=5.00] 1.178 .6068 -.011 2.367 3.768 1 .052
[group=.00] * [stimulation=5.00] * [delay_frames=10.00] .499 .5285 -.537 1.535 .892 1 .345
[group=.00] * [stimulation=5.00] * [delay_frames=15.00] .008 .3779 -.732 .749 .000 1 .982
[group=.00] * [stimulation=5.00] * [delay_frames=20.00] .199 .4356 -.655 1.053 .209 1 .647
[group=.00] * [stimulation=5.00] * [delay_frames=25.00] 0a . . . . . .
[group=.00] * [stimulation=7.00] * [delay_frames=.00] 0a . . . . . .
[group=.00] * [stimulation=7.00] * [delay_frames=5.00] 0a . . . . . .
[group=.00] * [stimulation=7.00] * [delay_frames=10.00] 0a . . . . . .
[group=.00] * [stimulation=7.00] * [delay_frames=15.00] 0a . . . . . .
[group=.00] * [stimulation=7.00] * [delay_frames=20.00] 0a . . . . . .
[group=.00] * [stimulation=7.00] * [delay_frames=25.00] 0a . . . . . .
[group=1.00] * [stimulation=1.00] * [delay_frames=.00] 0a . . . . . .
[group=1.00] * [stimulation=1.00] * [delay_frames=5.00] 0a . . . . . .
[group=1.00] * [stimulation=1.00] * [delay_frames=10.00] 0a . . . . . .
[group=1.00] * [stimulation=1.00] * [delay_frames=15.00] 0a . . . . . .
[group=1.00] * [stimulation=1.00] * [delay_frames=20.00] 0a . . . . . .
[group=1.00] * [stimulation=1.00] * [delay_frames=25.00] 0a . . . . . .
[group=1.00] * [stimulation=3.00] * [delay_frames=.00] 0a . . . . . .
[group=1.00] * [stimulation=3.00] * [delay_frames=5.00] 0a . . . . . .
[group=1.00] * [stimulation=3.00] * [delay_frames=10.00] 0a . . . . . .
[group=1.00] * [stimulation=3.00] * [delay_frames=15.00] 0a . . . . . .
[group=1.00] * [stimulation=3.00] * [delay_frames=20.00] 0a . . . . . .
[group=1.00] * [stimulation=3.00] * [delay_frames=25.00] 0a . . . . . .
[group=1.00] * [stimulation=5.00] * [delay_frames=.00] 0a . . . . . .
[group=1.00] * [stimulation=5.00] * [delay_frames=5.00] 0a . . . . . .
[group=1.00] * [stimulation=5.00] * [delay_frames=10.00] 0a . . . . . .
[group=1.00] * [stimulation=5.00] * [delay_frames=15.00] 0a . . . . . .
[group=1.00] * [stimulation=5.00] * [delay_frames=20.00] 0a . . . . . .
[group=1.00] * [stimulation=5.00] * [delay_frames=25.00] 0a . . . . . .
[group=1.00] * [stimulation=7.00] * [delay_frames=.00] 0a . . . . . .
[group=1.00] * [stimulation=7.00] * [delay_frames=5.00] 0a . . . . . .
[group=1.00] * [stimulation=7.00] * [delay_frames=10.00] 0a . . . . . .
[group=1.00] * [stimulation=7.00] * [delay_frames=15.00] 0a . . . . . .
[group=1.00] * [stimulation=7.00] * [delay_frames=20.00] 0a . . . . . .
[group=1.00] * [stimulation=7.00] * [delay_frames=25.00] 0a . . . . . .
[group=.00] * [condition=1.00] * [delay_frames=.00] 1.163 .5349 .115 2.212 4.729 1 .030
[group=.00] * [condition=1.00] * [delay_frames=5.00] .279 .4635 -.629 1.188 .363 1 .547
[group=.00] * [condition=1.00] * [delay_frames=10.00] .201 .5303 -.839 1.240 .143 1 .705
[group=.00] * [condition=1.00] * [delay_frames=15.00] -.193 .3865 -.950 .565 .249 1 .618
[group=.00] * [condition=1.00] * [delay_frames=20.00] -.204 .4502 -1.087 .678 .206 1 .650
[group=.00] * [condition=1.00] * [delay_frames=25.00] 0a . . . . . .
[group=.00] * [condition=2.00] * [delay_frames=.00] 0a . . . . . .
[group=.00] * [condition=2.00] * [delay_frames=5.00] 0a . . . . . .
[group=.00] * [condition=2.00] * [delay_frames=10.00] 0a . . . . . .
[group=.00] * [condition=2.00] * [delay_frames=15.00] 0a . . . . . .
[group=.00] * [condition=2.00] * [delay_frames=20.00] 0a . . . . . .
[group=.00] * [condition=2.00] * [delay_frames=25.00] 0a . . . . . .
[group=1.00] * [condition=1.00] * [delay_frames=.00] 0a . . . . . .
[group=1.00] * [condition=1.00] * [delay_frames=5.00] 0a . . . . . .
[group=1.00] * [condition=1.00] * [delay_frames=10.00] 0a . . . . . .
[group=1.00] * [condition=1.00] * [delay_frames=15.00] 0a . . . . . .
[group=1.00] * [condition=1.00] * [delay_frames=20.00] 0a . . . . . .
[group=1.00] * [condition=1.00] * [delay_frames=25.00] 0a . . . . . .
[group=1.00] * [condition=2.00] * [delay_frames=.00] 0a . . . . . .
[group=1.00] * [condition=2.00] * [delay_frames=5.00] 0a . . . . . .
[group=1.00] * [condition=2.00] * [delay_frames=10.00] 0a . . . . . .
[group=1.00] * [condition=2.00] * [delay_frames=15.00] 0a . . . . . .
[group=1.00] * [condition=2.00] * [delay_frames=20.00] 0a . . . . . .
[group=1.00] * [condition=2.00] * [delay_frames=25.00] 0a . . . . . .
[stimulation=1.00] * [condition=1.00] * [delay_frames=.00] .346 .4956 -.625 1.317 .487 1 .485
[stimulation=1.00] * [condition=1.00] * [delay_frames=5.00] -.099 .4351 -.952 .753 .052 1 .819
[stimulation=1.00] * [condition=1.00] * [delay_frames=10.00] -.640 .4314 -1.485 .206 2.199 1 .138
[stimulation=1.00] * [condition=1.00] * [delay_frames=15.00] -.538 .3211 -1.168 .091 2.811 1 .094
[stimulation=1.00] * [condition=1.00] * [delay_frames=20.00] -.717 .3547 -1.413 -.022 4.089 1 .043
[stimulation=1.00] * [condition=1.00] * [delay_frames=25.00] 0a . . . . . .
[stimulation=1.00] * [condition=2.00] * [delay_frames=.00] 0a . . . . . .
[stimulation=1.00] * [condition=2.00] * [delay_frames=5.00] 0a . . . . . .
[stimulation=1.00] * [condition=2.00] * [delay_frames=10.00] 0a . . . . . .
[stimulation=1.00] * [condition=2.00] * [delay_frames=15.00] 0a . . . . . .
[stimulation=1.00] * [condition=2.00] * [delay_frames=20.00] 0a . . . . . .
[stimulation=1.00] * [condition=2.00] * [delay_frames=25.00] 0a . . . . . .
[stimulation=3.00] * [condition=1.00] * [delay_frames=.00] .093 .7709 -1.418 1.604 .015 1 .904
[stimulation=3.00] * [condition=1.00] * [delay_frames=5.00] -1.247 .3513 -1.936 -.559 12.608 1 .000
[stimulation=3.00] * [condition=1.00] * [delay_frames=10.00] -.556 .4282 -1.395 .283 1.685 1 .194
[stimulation=3.00] * [condition=1.00] * [delay_frames=15.00] -.562 .1950 -.944 -.179 8.295 1 .004
[stimulation=3.00] * [condition=1.00] * [delay_frames=20.00] -.613 .4216 -1.439 .214 2.112 1 .146
[stimulation=3.00] * [condition=1.00] * [delay_frames=25.00] 0a . . . . . .
[stimulation=3.00] * [condition=2.00] * [delay_frames=.00] 0a . . . . . .
[stimulation=3.00] * [condition=2.00] * [delay_frames=5.00] 0a . . . . . .
[stimulation=3.00] * [condition=2.00] * [delay_frames=10.00] 0a . . . . . .
[stimulation=3.00] * [condition=2.00] * [delay_frames=15.00] 0a . . . . . .
[stimulation=3.00] * [condition=2.00] * [delay_frames=20.00] 0a . . . . . .
[stimulation=3.00] * [condition=2.00] * [delay_frames=25.00] 0a . . . . . .
[stimulation=5.00] * [condition=1.00] * [delay_frames=.00] .566 .4896 -.394 1.525 1.336 1 .248
[stimulation=5.00] * [condition=1.00] * [delay_frames=5.00] .203 .4426 -.664 1.071 .211 1 .646
[stimulation=5.00] * [condition=1.00] * [delay_frames=10.00] -.481 .4430 -1.349 .388 1.178 1 .278
[stimulation=5.00] * [condition=1.00] * [delay_frames=15.00] -.697 .2849 -1.255 -.138 5.977 1 .014
[stimulation=5.00] * [condition=1.00] * [delay_frames=20.00] -.369 .3591 -1.072 .335 1.053 1 .305
[stimulation=5.00] * [condition=1.00] * [delay_frames=25.00] 0a . . . . . .
[stimulation=5.00] * [condition=2.00] * [delay_frames=.00] 0a . . . . . .
[stimulation=5.00] * [condition=2.00] * [delay_frames=5.00] 0a . . . . . .
[stimulation=5.00] * [condition=2.00] * [delay_frames=10.00] 0a . . . . . .
[stimulation=5.00] * [condition=2.00] * [delay_frames=15.00] 0a . . . . . .
[stimulation=5.00] * [condition=2.00] * [delay_frames=20.00] 0a . . . . . .
[stimulation=5.00] * [condition=2.00] * [delay_frames=25.00] 0a . . . . . .
[stimulation=7.00] * [condition=1.00] * [delay_frames=.00] 0a . . . . . .
[stimulation=7.00] * [condition=1.00] * [delay_frames=5.00] 0a . . . . . .
[stimulation=7.00] * [condition=1.00] * [delay_frames=10.00] 0a . . . . . .
[stimulation=7.00] * [condition=1.00] * [delay_frames=15.00] 0a . . . . . .
[stimulation=7.00] * [condition=1.00] * [delay_frames=20.00] 0a . . . . . .
[stimulation=7.00] * [condition=1.00] * [delay_frames=25.00] 0a . . . . . .
[stimulation=7.00] * [condition=2.00] * [delay_frames=.00] 0a . . . . . .
[stimulation=7.00] * [condition=2.00] * [delay_frames=5.00] 0a . . . . . .
[stimulation=7.00] * [condition=2.00] * [delay_frames=10.00] 0a . . . . . .
[stimulation=7.00] * [condition=2.00] * [delay_frames=15.00] 0a . . . . . .
[stimulation=7.00] * [condition=2.00] * [delay_frames=20.00] 0a . . . . . .
[stimulation=7.00] * [condition=2.00] * [delay_frames=25.00] 0a . . . . . .
[group=.00] * [stimulation=1.00] * [condition=1.00] * [delay_frames=.00] -.740 .7014 -2.115 .634 1.114 1 .291
[group=.00] * [stimulation=1.00] * [condition=1.00] * [delay_frames=5.00] .017 .6513 -1.259 1.294 .001 1 .979
[group=.00] * [stimulation=1.00] * [condition=1.00] * [delay_frames=10.00] .422 .5499 -.656 1.499 .588 1 .443
[group=.00] * [stimulation=1.00] * [condition=1.00] * [delay_frames=15.00] .248 .4449 -.624 1.120 .311 1 .577
[group=.00] * [stimulation=1.00] * [condition=1.00] * [delay_frames=20.00] .300 .5564 -.790 1.391 .291 1 .589
[group=.00] * [stimulation=1.00] * [condition=1.00] * [delay_frames=25.00] 0a . . . . . .
[group=.00] * [stimulation=1.00] * [condition=2.00] * [delay_frames=.00] 0a . . . . . .
[group=.00] * [stimulation=1.00] * [condition=2.00] * [delay_frames=5.00] 0a . . . . . .
[group=.00] * [stimulation=1.00] * [condition=2.00] * [delay_frames=10.00] 0a . . . . . .
[group=.00] * [stimulation=1.00] * [condition=2.00] * [delay_frames=15.00] 0a . . . . . .
[group=.00] * [stimulation=1.00] * [condition=2.00] * [delay_frames=20.00] 0a . . . . . .
[group=.00] * [stimulation=1.00] * [condition=2.00] * [delay_frames=25.00] 0a . . . . . .
[group=.00] * [stimulation=3.00] * [condition=1.00] * [delay_frames=.00] -.583 .9431 -2.431 1.266 .382 1 .537
[group=.00] * [stimulation=3.00] * [condition=1.00] * [delay_frames=5.00] .756 .6073 -.434 1.946 1.549 1 .213
[group=.00] * [stimulation=3.00] * [condition=1.00] * [delay_frames=10.00] .123 .5883 -1.030 1.276 .044 1 .834
[group=.00] * [stimulation=3.00] * [condition=1.00] * [delay_frames=15.00] .322 .4592 -.578 1.222 .492 1 .483
[group=.00] * [stimulation=3.00] * [condition=1.00] * [delay_frames=20.00] .621 .7197 -.789 2.032 .746 1 .388
[group=.00] * [stimulation=3.00] * [condition=1.00] * [delay_frames=25.00] 0a . . . . . .
[group=.00] * [stimulation=3.00] * [condition=2.00] * [delay_frames=.00] 0a . . . . . .
[group=.00] * [stimulation=3.00] * [condition=2.00] * [delay_frames=5.00] 0a . . . . . .
[group=.00] * [stimulation=3.00] * [condition=2.00] * [delay_frames=10.00] 0a . . . . . .
[group=.00] * [stimulation=3.00] * [condition=2.00] * [delay_frames=15.00] 0a . . . . . .
[group=.00] * [stimulation=3.00] * [condition=2.00] * [delay_frames=20.00] 0a . . . . . .
[group=.00] * [stimulation=3.00] * [condition=2.00] * [delay_frames=25.00] 0a . . . . . .
[group=.00] * [stimulation=5.00] * [condition=1.00] * [delay_frames=.00] -1.224 .7391 -2.673 .224 2.743 1 .098
[group=.00] * [stimulation=5.00] * [condition=1.00] * [delay_frames=5.00] -.181 .6712 -1.496 1.135 .073 1 .788
[group=.00] * [stimulation=5.00] * [condition=1.00] * [delay_frames=10.00] .381 .6524 -.898 1.659 .340 1 .560
[group=.00] * [stimulation=5.00] * [condition=1.00] * [delay_frames=15.00] 1.195 .4629 .288 2.102 6.663 1 .010
[group=.00] * [stimulation=5.00] * [condition=1.00] * [delay_frames=20.00] .623 .6162 -.585 1.831 1.022 1 .312
[group=.00] * [stimulation=5.00] * [condition=1.00] * [delay_frames=25.00] 0a . . . . . .
[group=.00] * [stimulation=5.00] * [condition=2.00] * [delay_frames=.00] 0a . . . . . .
[group=.00] * [stimulation=5.00] * [condition=2.00] * [delay_frames=5.00] 0a . . . . . .
[group=.00] * [stimulation=5.00] * [condition=2.00] * [delay_frames=10.00] 0a . . . . . .
[group=.00] * [stimulation=5.00] * [condition=2.00] * [delay_frames=15.00] 0a . . . . . .
[group=.00] * [stimulation=5.00] * [condition=2.00] * [delay_frames=20.00] 0a . . . . . .
[group=.00] * [stimulation=5.00] * [condition=2.00] * [delay_frames=25.00] 0a . . . . . .
[group=.00] * [stimulation=7.00] * [condition=1.00] * [delay_frames=.00] 0a . . . . . .
[group=.00] * [stimulation=7.00] * [condition=1.00] * [delay_frames=5.00] 0a . . . . . .
[group=.00] * [stimulation=7.00] * [condition=1.00] * [delay_frames=10.00] 0a . . . . . .
[group=.00] * [stimulation=7.00] * [condition=1.00] * [delay_frames=15.00] 0a . . . . . .
[group=.00] * [stimulation=7.00] * [condition=1.00] * [delay_frames=20.00] 0a . . . . . .
[group=.00] * [stimulation=7.00] * [condition=1.00] * [delay_frames=25.00] 0a . . . . . .
[group=.00] * [stimulation=7.00] * [condition=2.00] * [delay_frames=.00] 0a . . . . . .
[group=.00] * [stimulation=7.00] * [condition=2.00] * [delay_frames=5.00] 0a . . . . . .
[group=.00] * [stimulation=7.00] * [condition=2.00] * [delay_frames=10.00] 0a . . . . . .
[group=.00] * [stimulation=7.00] * [condition=2.00] * [delay_frames=15.00] 0a . . . . . .
[group=.00] * [stimulation=7.00] * [condition=2.00] * [delay_frames=20.00] 0a . . . . . .
[group=.00] * [stimulation=7.00] * [condition=2.00] * [delay_frames=25.00] 0a . . . . . .
[group=1.00] * [stimulation=1.00] * [condition=1.00] * [delay_frames=.00] 0a . . . . . .
[group=1.00] * [stimulation=1.00] * [condition=1.00] * [delay_frames=5.00] 0a . . . . . .
[group=1.00] * [stimulation=1.00] * [condition=1.00] * [delay_frames=10.00] 0a . . . . . .
[group=1.00] * [stimulation=1.00] * [condition=1.00] * [delay_frames=15.00] 0a . . . . . .
[group=1.00] * [stimulation=1.00] * [condition=1.00] * [delay_frames=20.00] 0a . . . . . .
[group=1.00] * [stimulation=1.00] * [condition=1.00] * [delay_frames=25.00] 0a . . . . . .
[group=1.00] * [stimulation=1.00] * [condition=2.00] * [delay_frames=.00] 0a . . . . . .
[group=1.00] * [stimulation=1.00] * [condition=2.00] * [delay_frames=5.00] 0a . . . . . .
[group=1.00] * [stimulation=1.00] * [condition=2.00] * [delay_frames=10.00] 0a . . . . . .
[group=1.00] * [stimulation=1.00] * [condition=2.00] * [delay_frames=15.00] 0a . . . . . .
[group=1.00] * [stimulation=1.00] * [condition=2.00] * [delay_frames=20.00] 0a . . . . . .
[group=1.00] * [stimulation=1.00] * [condition=2.00] * [delay_frames=25.00] 0a . . . . . .
[group=1.00] * [stimulation=3.00] * [condition=1.00] * [delay_frames=.00] 0a . . . . . .
[group=1.00] * [stimulation=3.00] * [condition=1.00] * [delay_frames=5.00] 0a . . . . . .
[group=1.00] * [stimulation=3.00] * [condition=1.00] * [delay_frames=10.00] 0a . . . . . .
[group=1.00] * [stimulation=3.00] * [condition=1.00] * [delay_frames=15.00] 0a . . . . . .
[group=1.00] * [stimulation=3.00] * [condition=1.00] * [delay_frames=20.00] 0a . . . . . .
[group=1.00] * [stimulation=3.00] * [condition=1.00] * [delay_frames=25.00] 0a . . . . . .
[group=1.00] * [stimulation=3.00] * [condition=2.00] * [delay_frames=.00] 0a . . . . . .
[group=1.00] * [stimulation=3.00] * [condition=2.00] * [delay_frames=5.00] 0a . . . . . .
[group=1.00] * [stimulation=3.00] * [condition=2.00] * [delay_frames=10.00] 0a . . . . . .
[group=1.00] * [stimulation=3.00] * [condition=2.00] * [delay_frames=15.00] 0a . . . . . .
[group=1.00] * [stimulation=3.00] * [condition=2.00] * [delay_frames=20.00] 0a . . . . . .
[group=1.00] * [stimulation=3.00] * [condition=2.00] * [delay_frames=25.00] 0a . . . . . .
[group=1.00] * [stimulation=5.00] * [condition=1.00] * [delay_frames=.00] 0a . . . . . .
[group=1.00] * [stimulation=5.00] * [condition=1.00] * [delay_frames=5.00] 0a . . . . . .
[group=1.00] * [stimulation=5.00] * [condition=1.00] * [delay_frames=10.00] 0a . . . . . .
[group=1.00] * [stimulation=5.00] * [condition=1.00] * [delay_frames=15.00] 0a . . . . . .
[group=1.00] * [stimulation=5.00] * [condition=1.00] * [delay_frames=20.00] 0a . . . . . .
[group=1.00] * [stimulation=5.00] * [condition=1.00] * [delay_frames=25.00] 0a . . . . . .
[group=1.00] * [stimulation=5.00] * [condition=2.00] * [delay_frames=.00] 0a . . . . . .
[group=1.00] * [stimulation=5.00] * [condition=2.00] * [delay_frames=5.00] 0a . . . . . .
[group=1.00] * [stimulation=5.00] * [condition=2.00] * [delay_frames=10.00] 0a . . . . . .
[group=1.00] * [stimulation=5.00] * [condition=2.00] * [delay_frames=15.00] 0a . . . . . .
[group=1.00] * [stimulation=5.00] * [condition=2.00] * [delay_frames=20.00] 0a . . . . . .
[group=1.00] * [stimulation=5.00] * [condition=2.00] * [delay_frames=25.00] 0a . . . . . .
[group=1.00] * [stimulation=7.00] * [condition=1.00] * [delay_frames=.00] 0a . . . . . .
[group=1.00] * [stimulation=7.00] * [condition=1.00] * [delay_frames=5.00] 0a . . . . . .
[group=1.00] * [stimulation=7.00] * [condition=1.00] * [delay_frames=10.00] 0a . . . . . .
[group=1.00] * [stimulation=7.00] * [condition=1.00] * [delay_frames=15.00] 0a . . . . . .
[group=1.00] * [stimulation=7.00] * [condition=1.00] * [delay_frames=20.00] 0a . . . . . .
[group=1.00] * [stimulation=7.00] * [condition=1.00] * [delay_frames=25.00] 0a . . . . . .
[group=1.00] * [stimulation=7.00] * [condition=2.00] * [delay_frames=.00] 0a . . . . . .
[group=1.00] * [stimulation=7.00] * [condition=2.00] * [delay_frames=5.00] 0a . . . . . .
[group=1.00] * [stimulation=7.00] * [condition=2.00] * [delay_frames=10.00] 0a . . . . . .
[group=1.00] * [stimulation=7.00] * [condition=2.00] * [delay_frames=15.00] 0a . . . . . .
[group=1.00] * [stimulation=7.00] * [condition=2.00] * [delay_frames=20.00] 0a . . . . . .
[group=1.00] * [stimulation=7.00] * [condition=2.00] * [delay_frames=25.00] 0a . . . . . .
(Skala) 1            
Abhängige Variable: response
Modell: (Konstanter Term), group, stimulation, condition, delay_frames, group * stimulation, group * condition, group * delay_frames, stimulation * condition, stimulation * delay_frames, condition * delay_frames, group * stimulation * condition, group * stimulation * delay_frames, group * condition * delay_frames, stimulation * condition * delay_frames, group * stimulation * condition * delay_frames
a. Auf 0 gesetzt, da dieser Parameter redundant ist.


Geschätzte Randmittel 1: group* stimulation* condition* delay_frames


Schätzer
group stimulation condition delay_frames Mittelwert Standardfehler 95% Wald-Konfidenzintervall
Unterer Wert Oberer Wert
dimension0 HC dimension1 LFC-RFA dimension2 active dimension3 .00 .19 .045 .10 .27
5.00 .29 .065 .16 .42
10.00 .53 .073 .39 .68
15.00 .70 .056 .59 .80
20.00 .76 .052 .66 .86
25.00 .88 .033 .81 .95
passive dimension3 .00 .18 .043 .09 .26
5.00 .20 .054 .10 .31
10.00 .43 .062 .31 .56
15.00 .63 .060 .51 .75
20.00 .74 .053 .64 .85
25.00 .82 .041 .74 .90
LPC-RPA dimension2 active dimension3 .00 .16 .036 .09 .23
5.00 .29 .050 .19 .39
10.00 .50 .062 .38 .62
15.00 .71 .048 .61 .80
20.00 .81 .045 .72 .90
25.00 .89 .029 .84 .95
passive dimension3 .00 .17 .040 .09 .24
5.00 .27 .045 .19 .36
10.00 .45 .064 .33 .58
15.00 .63 .057 .52 .74
20.00 .72 .049 .62 .81
25.00 .84 .039 .76 .92
LFC-RPA dimension2 active dimension3 .00 .12 .030 .06 .18
5.00 .31 .059 .19 .43
10.00 .47 .068 .34 .60
15.00 .68 .056 .57 .79
20.00 .79 .049 .70 .89
25.00 .85 .037 .78 .93
passive dimension3 .00 .21 .047 .12 .31
5.00 .29 .055 .18 .39
10.00 .46 .063 .33 .58
15.00 .53 .061 .41 .65
20.00 .74 .044 .65 .83
25.00 .85 .033 .79 .92
sham dimension2 active dimension3 .00 .10 .031 .04 .16
5.00 .20 .035 .13 .27
10.00 .47 .058 .36 .58
15.00 .66 .057 .55 .77
20.00 .82 .034 .76 .89
25.00 .88 .030 .83 .94
passive dimension3 .00 .09 .025 .04 .14
5.00 .17 .042 .09 .25
10.00 .40 .057 .29 .51
15.00 .60 .063 .48 .73
20.00 .80 .041 .72 .88
25.00 .87 .033 .81 .94
SSD dimension1 LFC-RFA dimension2 active dimension3 .00 .05 .022 .01 .10
5.00 .11 .030 .05 .17
10.00 .22 .054 .12 .33
15.00 .46 .069 .33 .60
20.00 .60 .073 .46 .75
25.00 .74 .071 .60 .88
passive dimension3 .00 .08 .029 .02 .13
5.00 .09 .034 .03 .16
10.00 .26 .042 .18 .35
15.00 .40 .052 .30 .51
20.00 .61 .068 .48 .74
25.00 .65 .061 .53 .77
LPC-RPA dimension2 active dimension3 .00 .06 .024 .02 .11
5.00 .07 .023 .02 .11
10.00 .28 .052 .18 .38
15.00 .51 .072 .37 .65
20.00 .65 .076 .50 .80
25.00 .74 .074 .60 .89
passive dimension3 .00 .09 .036 .02 .17
5.00 .13 .038 .06 .21
10.00 .27 .053 .17 .37
15.00 .41 .073 .26 .55
20.00 .57 .077 .42 .73
25.00 .60 .079 .44 .75
LFC-RPA dimension2 active dimension3 .00 .10 .032 .04 .16
5.00 .16 .043 .08 .25
10.00 .27 .060 .15 .39
15.00 .46 .080 .30 .62
20.00 .57 .062 .45 .70
25.00 .76 .062 .64 .89
passive dimension3 .00 .14 .047 .05 .23
5.00 .13 .041 .05 .21
10.00 .33 .062 .21 .45
15.00 .49 .074 .35 .64
20.00 .55 .075 .40 .69
25.00 .72 .073 .58 .86
sham dimension2 active dimension3 .00 .07 .024 .02 .11
5.00 .12 .035 .05 .19
10.00 .28 .059 .17 .40
15.00 .54 .072 .40 .68
20.00 .63 .073 .48 .77
25.00 .65 .071 .51 .79
passive dimension3 .00 .18 .045 .09 .26
5.00 .13 .038 .05 .20
10.00 .27 .055 .16 .38
15.00 .44 .060 .32 .55
20.00 .55 .075 .40 .69
25.00 .63 .079 .48 .79

Paarweise Vergleiche
(I)group*stimulation*condition*delay_frames (J)group*stimulation*condition*delay_frames Mittlere Differenz (I-J) Standardfehler df Sig. 95% Wald-Konfidenzintervall für die Differenz
Unterer Wert Oberer Wert
[group=.00]*[stimulation=1.00]*[condition=1.00]*[delay_frames=.00] [group=.00]*[stimulation=1.00]*[condition=1.00]*[delay_frames=5.00] -.11a .048 1 .027 -.20 -.01
[group=.00]*[stimulation=1.00]*[condition=1.00]*[delay_frames=10.00] -.35a .068 1 .000 -.48 -.21
[group=.00]*[stimulation=1.00]*[condition=1.00]*[delay_frames=15.00] -.51a .059 1 .000 -.63 -.39
[group=.00]*[stimulation=1.00]*[condition=1.00]*[delay_frames=20.00] -.57a .073 1 .000 -.72 -.43
[group=.00]*[stimulation=1.00]*[condition=1.00]*[delay_frames=25.00] -.69a .056 1 .000 -.80 -.58
[group=.00]*[stimulation=1.00]*[condition=2.00]*[delay_frames=.00] .01 .039 1 .805 -.07 .09
[group=.00]*[stimulation=1.00]*[condition=2.00]*[delay_frames=5.00] -.02 .053 1 .722 -.12 .09
[group=.00]*[stimulation=1.00]*[condition=2.00]*[delay_frames=10.00] -.25a .057 1 .000 -.36 -.14
[group=.00]*[stimulation=1.00]*[condition=2.00]*[delay_frames=15.00] -.44a .065 1 .000 -.57 -.32
[group=.00]*[stimulation=1.00]*[condition=2.00]*[delay_frames=20.00] -.56a .063 1 .000 -.68 -.43
[group=.00]*[stimulation=1.00]*[condition=2.00]*[delay_frames=25.00] -.64a .059 1 .000 -.75 -.52
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[group=1.00]*[stimulation=5.00]*[condition=2.00]*[delay_frames=20.00] .08 .097 1 .397 -.11 .27
[group=1.00]*[stimulation=5.00]*[condition=2.00]*[delay_frames=25.00] -.09 .095 1 .343 -.28 .10
[group=1.00]*[stimulation=7.00]*[condition=1.00]*[delay_frames=.00] .56a .065 1 .000 .43 .69
[group=1.00]*[stimulation=7.00]*[condition=1.00]*[delay_frames=5.00] .51a .070 1 .000 .37 .65
[group=1.00]*[stimulation=7.00]*[condition=1.00]*[delay_frames=10.00] .35a .084 1 .000 .18 .51
[group=1.00]*[stimulation=7.00]*[condition=1.00]*[delay_frames=15.00] .09 .094 1 .337 -.09 .27
[group=1.00]*[stimulation=7.00]*[condition=1.00]*[delay_frames=20.00] .00 .095 1 .986 -.18 .19
[group=1.00]*[stimulation=7.00]*[condition=1.00]*[delay_frames=25.00] -.02 .093 1 .797 -.21 .16
[group=1.00]*[stimulation=7.00]*[condition=2.00]*[delay_frames=.00] .45a .075 1 .000 .31 .60
[group=1.00]*[stimulation=7.00]*[condition=2.00]*[delay_frames=5.00] .50a .071 1 .000 .36 .64
[group=1.00]*[stimulation=7.00]*[condition=2.00]*[delay_frames=10.00] .36a .082 1 .000 .20 .52
[group=1.00]*[stimulation=7.00]*[condition=2.00]*[delay_frames=15.00] .19a .085 1 .024 .02 .36
[group=1.00]*[stimulation=7.00]*[condition=2.00]*[delay_frames=20.00] .08 .096 1 .395 -.11 .27
[group=1.00]*[stimulation=7.00]*[condition=2.00]*[delay_frames=25.00] .00 .099 1 .961 -.20 .19
[group=.00]*[stimulation=1.00]*[condition=2.00]*[delay_frames=20.00] [group=.00]*[stimulation=1.00]*[condition=1.00]*[delay_frames=.00] .56a .063 1 .000 .43 .68
[group=.00]*[stimulation=1.00]*[condition=1.00]*[delay_frames=5.00] .45a .067 1 .000 .32 .58
[group=.00]*[stimulation=1.00]*[condition=1.00]*[delay_frames=10.00] .21a .068 1 .002 .08 .34
[group=.00]*[stimulation=1.00]*[condition=1.00]*[delay_frames=15.00] .05 .061 1 .433 -.07 .17
[group=.00]*[stimulation=1.00]*[condition=1.00]*[delay_frames=20.00] -.02 .061 1 .796 -.14 .10
[group=.00]*[stimulation=1.00]*[condition=1.00]*[delay_frames=25.00] -.14a .053 1 .011 -.24 -.03
[group=.00]*[stimulation=1.00]*[condition=2.00]*[delay_frames=.00] .57a .058 1 .000 .45 .68
[group=.00]*[stimulation=1.00]*[condition=2.00]*[delay_frames=5.00] .54a .058 1 .000 .42 .65
[group=.00]*[stimulation=1.00]*[condition=2.00]*[delay_frames=10.00] .31a .056 1 .000 .20 .42
[group=.00]*[stimulation=1.00]*[condition=2.00]*[delay_frames=15.00] .11a .043 1 .007 .03 .20
[group=.00]*[stimulation=1.00]*[condition=2.00]*[delay_frames=25.00] -.08a .034 1 .020 -.15 -.01
[group=.00]*[stimulation=3.00]*[condition=1.00]*[delay_frames=.00] .58a .055 1 .000 .47 .69
[group=.00]*[stimulation=3.00]*[condition=1.00]*[delay_frames=5.00] .46a .058 1 .000 .34 .57
[group=.00]*[stimulation=3.00]*[condition=1.00]*[delay_frames=10.00] .24a .059 1 .000 .13 .36
[group=.00]*[stimulation=3.00]*[condition=1.00]*[delay_frames=15.00] .04 .050 1 .471 -.06 .13
[group=.00]*[stimulation=3.00]*[condition=1.00]*[delay_frames=20.00] -.07 .061 1 .262 -.19 .05
[group=.00]*[stimulation=3.00]*[condition=1.00]*[delay_frames=25.00] -.15a .050 1 .003 -.25 -.05
[group=.00]*[stimulation=3.00]*[condition=2.00]*[delay_frames=.00] .58a .058 1 .000 .46 .69
[group=.00]*[stimulation=3.00]*[condition=2.00]*[delay_frames=5.00] .47a .055 1 .000 .36 .58
[group=.00]*[stimulation=3.00]*[condition=2.00]*[delay_frames=10.00] .29a .055 1 .000 .18 .40
[group=.00]*[stimulation=3.00]*[condition=2.00]*[delay_frames=15.00] .12a .050 1 .022 .02 .21
[group=.00]*[stimulation=3.00]*[condition=2.00]*[delay_frames=20.00] .02 .033 1 .463 -.04 .09
[group=.00]*[stimulation=3.00]*[condition=2.00]*[delay_frames=25.00] -.10a .038 1 .010 -.17 -.02
[group=.00]*[stimulation=5.00]*[condition=1.00]*[delay_frames=.00] .62a .062 1 .000 .50 .74
[group=.00]*[stimulation=5.00]*[condition=1.00]*[delay_frames=5.00] .43a .066 1 .000 .30 .56
[group=.00]*[stimulation=5.00]*[condition=1.00]*[delay_frames=10.00] .27a .066 1 .000 .14 .40
[group=.00]*[stimulation=5.00]*[condition=1.00]*[delay_frames=15.00] .07 .062 1 .279 -.05 .19
[group=.00]*[stimulation=5.00]*[condition=1.00]*[delay_frames=20.00] -.05 .060 1 .403 -.17 .07
[group=.00]*[stimulation=5.00]*[condition=1.00]*[delay_frames=25.00] -.11a .050 1 .025 -.21 -.01
[group=.00]*[stimulation=5.00]*[condition=2.00]*[delay_frames=.00] .53a .069 1 .000 .40 .67
[group=.00]*[stimulation=5.00]*[condition=2.00]*[delay_frames=5.00] .46a .063 1 .000 .33 .58
[group=.00]*[stimulation=5.00]*[condition=2.00]*[delay_frames=10.00] .29a .064 1 .000 .16 .41
[group=.00]*[stimulation=5.00]*[condition=2.00]*[delay_frames=15.00] .22a .062 1 .001 .09 .34
[group=.00]*[stimulation=5.00]*[condition=2.00]*[delay_frames=20.00] .00 .040 1 .937 -.07 .08
[group=.00]*[stimulation=5.00]*[condition=2.00]*[delay_frames=25.00] -.11a .040 1 .005 -.19 -.03
[group=.00]*[stimulation=7.00]*[condition=1.00]*[delay_frames=.00] .64a .058 1 .000 .53 .76
[group=.00]*[stimulation=7.00]*[condition=1.00]*[delay_frames=5.00] .54a .061 1 .000 .42 .66
[group=.00]*[stimulation=7.00]*[condition=1.00]*[delay_frames=10.00] .27a .064 1 .000 .15 .40
[group=.00]*[stimulation=7.00]*[condition=1.00]*[delay_frames=15.00] .08 .061 1 .168 -.04 .20
[group=.00]*[stimulation=7.00]*[condition=1.00]*[delay_frames=20.00] -.08 .054 1 .128 -.19 .02
[group=.00]*[stimulation=7.00]*[condition=1.00]*[delay_frames=25.00] -.14a .057 1 .013 -.25 -.03
[group=.00]*[stimulation=7.00]*[condition=2.00]*[delay_frames=.00] .65a .057 1 .000 .54 .77
[group=.00]*[stimulation=7.00]*[condition=2.00]*[delay_frames=5.00] .57a .064 1 .000 .45 .70
[group=.00]*[stimulation=7.00]*[condition=2.00]*[delay_frames=10.00] .34a .057 1 .000 .23 .45
[group=.00]*[stimulation=7.00]*[condition=2.00]*[delay_frames=15.00] .14a .055 1 .011 .03 .25
[group=.00]*[stimulation=7.00]*[condition=2.00]*[delay_frames=20.00] -.06 .042 1 .165 -.14 .02
[group=.00]*[stimulation=7.00]*[condition=2.00]*[delay_frames=25.00] -.13a .039 1 .001 -.21 -.05
[group=1.00]*[stimulation=1.00]*[condition=1.00]*[delay_frames=.00] .69a .057 1 .000 .58 .80
[group=1.00]*[stimulation=1.00]*[condition=1.00]*[delay_frames=5.00] .63a .061 1 .000 .52 .75
[group=1.00]*[stimulation=1.00]*[condition=1.00]*[delay_frames=10.00] .52a .075 1 .000 .37 .67
[group=1.00]*[stimulation=1.00]*[condition=1.00]*[delay_frames=15.00] .28a .087 1 .001 .11 .45
[group=1.00]*[stimulation=1.00]*[cond