knitr::opts_chunk$set(warning = TRUE, message = TRUE, echo = FALSE, error = FALSE)
pander::panderOptions("table.split.table", Inf)
library(codebook)
data("bfi", package = 'codebook')
bfi2 = zap_attributes(bfi)
bfi2[,1:5] <- bfi[,1:5]
bfi <- bfi2
bfi$age <- 1:nrow(bfi)
bfi$abode <- rep("my happy place", times = nrow(bfi))
latent <- rnorm(nrow(bfi))
bfi$normal1 <- latent + rnorm(nrow(bfi))
bfi$normal2 <- latent + rnorm(nrow(bfi))
bfi$normal3 <- latent + rnorm(nrow(bfi))
bfi$normal4 <- latent + rnorm(nrow(bfi))
bfi$normal <- bfi %>% dplyr::select(dplyr::starts_with("normal")) %>% rowMeans()
var_label(bfi$abode) <- "Where do you live?"
bfi$uniq_id <- as.character(1:nrow(bfi))
var_label(bfi$uniq_id) <- "Unique ID"
ggplot2::theme_set(ggplot2::theme_bw())
pander::panderOptions("table.split.table", Inf)
bfi$age <- rpois(nrow(bfi), 30)
# class(bfi$age) = c("udhfibr")
bfi <- detect_scales(bfi)
#> 4 BFIK_open items connected to scale
#> 4 BFIK_agree items connected to scale
#> 4 BFIK_extra items connected to scale
#> 3 BFIK_neuro items connected to scale
#> 4 BFIK_consc items connected to scale
#> 4 normal items connected to scale
Dataset name: bfi
The dataset has N=28 rows and 37 columns. 0 rows have no missing values on any column.
Metadata for search engines
Date published: 2019-02-21
28 completed rows, 28 who entered any information, 0 only viewed the first page. There are 0 expired rows (people who did not finish filling out in the requested time frame). In total, there are 28 rows including unfinished and expired rows.
There were 28 unique participants, of which 28 finished filling out at least one survey.
This survey was not repeated.
The first session started on 2016-07-08 09:54:16, the last session on 2016-11-02 21:19:50.
#> `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
People took on average 127.36 minutes (median 1.48) to answer the survey.
#> Warning: Durations below 0 detected.
#> Warning: Removed 4 rows containing non-finite values (stat_bin).
#> Warning: Removed 2 rows containing missing values (geom_bar).
Reliability: ωordinal [95% CI] = 0.61 [0.37;0.84].
Missing: 0.
| Index | Estimate |
|---|---|
| Omega | 0.8193 |
| Omega Psych Tot | 0.8878 |
| Omega Psych H | 0.7664 |
| Omega Ordinal | 0.605 |
| Cronbach Alpha | 0.8006 |
| Greatest Lower Bound | 0.8858 |
| Alpha Ordinal | 0.5879 |
Positive correlations: 6 out of 6 (100%)
Detailed output
#>
#> Information about this analysis:
#>
#> Dataframe: res$dat
#> Items: BFIK_agree_4R, BFIK_agree_1R, BFIK_agree_3R, BFIK_agree_2
#> Observations: 28
#> Positive correlations: 6 out of 6 (100%)
#>
#> Estimates assuming interval level:
#>
#> Omega (total): 0.82
#> Omega (hierarchical): 0.77
#> Revelle's omega (total): 0.89
#> Greatest Lower Bound (GLB): 0.89
#> Coefficient H: 0.88
#> Cronbach's alpha: 0.8
#> Confidence intervals:
#> Omega (total): [0.71, 0.93]
#> Cronbach's alpha: [0.68, 0.92]
#>
#> Estimates assuming ordinal level:
#>
#> Ordinal Omega (total): 0.61
#> Ordinal Omega (hierarch.): 0.59
#> Ordinal Cronbach's alpha: 0.59
#> Confidence intervals:
#> Ordinal Omega (total): [0.37, 0.84]
#> Ordinal Cronbach's alpha: [0.33, 0.84]
#>
#> Note: the normal point estimate and confidence interval for omega are based on the procedure suggested by Dunn, Baguley & Brunsden (2013) using the MBESS function ci.reliability, whereas the psych package point estimate was suggested in Revelle & Zinbarg (2008). See the help ('?scaleStructure') for more information.
#>
#> Eigen values: 2.539, 0.732, 0.54, 0.189
#> Loadings:
#> PC1
#> BFIK_agree_4R 0.871
#> BFIK_agree_1R 0.748
#> BFIK_agree_3R 0.880
#> BFIK_agree_2 0.668
#>
#> PC1
#> SS loadings 2.539
#> Proportion Var 0.635
#>
#> vars n mean sd median trimmed mad min max range skew
#> BFIK_agree_4R 1 28 2.93 1.18 3 2.92 1.48 1 5 4 0.26
#> BFIK_agree_1R 2 28 3.00 0.94 3 2.96 1.48 2 5 3 0.26
#> BFIK_agree_3R 3 28 3.04 1.29 3 3.04 1.48 1 5 4 0.04
#> BFIK_agree_2 4 28 3.50 1.26 4 3.58 1.48 1 5 4 -0.43
#> kurtosis se
#> BFIK_agree_4R -1.18 0.22
#> BFIK_agree_1R -1.37 0.18
#> BFIK_agree_3R -1.35 0.24
#> BFIK_agree_2 -1.03 0.24
| name | data_type | missing | complete | n | mean | sd | p0 | p25 | p50 | p75 | p100 | hist |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| BFIK_agree_4R | numeric | 0 | 28 | 28 | 2.93 | 1.18 | 1 | 2 | 3 | 4 | 5 | ▂▇▁▃▁▅▁▂ |
| BFIK_agree_1R | numeric | 0 | 28 | 28 | 3 | 0.94 | 2 | 2 | 3 | 4 | 5 | ▇▁▅▁▁▆▁▁ |
| BFIK_agree_3R | numeric | 0 | 28 | 28 | 3.04 | 1.29 | 1 | 2 | 3 | 4 | 5 | ▂▇▁▃▁▇▁▃ |
| BFIK_agree_2 | numeric | 0 | 28 | 28 | 3.5 | 1.26 | 1 | 2.75 | 4 | 4.25 | 5 | ▂▅▁▅▁▇▁▆ |
Reliability: ωtotal [95% CI] = 166.85 [not computed].
Missing: 0.
| Index | Estimate |
|---|---|
| Omega | 166.8 |
| Omega Psych Tot | 0.4603 |
| Omega Psych H | 0.2493 |
| Cronbach Alpha | 0.5271 |
| Greatest Lower Bound | 0.7231 |
Positive correlations: 5 out of 6 (83%)
Detailed output
#>
#> Information about this analysis:
#>
#> Dataframe: res$dat
#> Items: BFIK_open_2, BFIK_open_1, BFIK_open_4, BFIK_open_3
#> Observations: 28
#> Positive correlations: 5 out of 6 (83%)
#>
#> Estimates assuming interval level:
#>
#> Omega (total): 166.85
#> Omega (hierarchical): 0.25
#> Revelle's omega (total): 0.46
#> Greatest Lower Bound (GLB): 0.72
#> Coefficient H: 1
#> Cronbach's alpha: 0.53
#>
#> Estimates assuming ordinal level:
#>
#> Ordinal Omega (total): 0.65
#> Ordinal Omega (hierarch.): 0.62
#> Ordinal Cronbach's alpha: 0.64
#>
#> Note: the normal point estimate and confidence interval for omega are based on the procedure suggested by Dunn, Baguley & Brunsden (2013) using the MBESS function ci.reliability, whereas the psych package point estimate was suggested in Revelle & Zinbarg (2008). See the help ('?scaleStructure') for more information.
#>
#> Eigen values: 1.697, 1.074, 0.881, 0.349
#> Loadings:
#> TC1 TC2
#> BFIK_open_2 0.280 0.492
#> BFIK_open_1 0.916
#> BFIK_open_4 0.922 -0.168
#> BFIK_open_3 0.809 0.239
#>
#> TC1 TC2
#> SS loadings 1.585 1.167
#> Proportion Var 0.396 0.292
#> Cumulative Var 0.396 0.688
#>
#> vars n mean sd median trimmed mad min max range skew
#> BFIK_open_2 1 28 4.21 0.74 4.0 4.29 0.00 2 5 3 -0.86
#> BFIK_open_1 2 28 4.39 0.83 5.0 4.50 0.00 2 5 3 -1.16
#> BFIK_open_4 3 28 4.21 0.96 4.0 4.33 1.48 1 5 4 -1.39
#> BFIK_open_3 4 28 4.21 0.96 4.5 4.33 0.74 2 5 3 -0.90
#> kurtosis se
#> BFIK_open_2 0.88 0.14
#> BFIK_open_1 0.47 0.16
#> BFIK_open_4 2.13 0.18
#> BFIK_open_3 -0.35 0.18
| name | data_type | missing | complete | n | mean | sd | p0 | p25 | p50 | p75 | p100 | hist |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| BFIK_open_2 | numeric | 0 | 28 | 28 | 4.21 | 0.74 | 2 | 4 | 4 | 5 | 5 | ▁▁▁▁▁▇▁▅ |
| BFIK_open_1 | numeric | 0 | 28 | 28 | 4.39 | 0.83 | 2 | 4 | 5 | 5 | 5 | ▁▁▂▁▁▃▁▇ |
| BFIK_open_4 | numeric | 0 | 28 | 28 | 4.21 | 0.96 | 1 | 4 | 4 | 5 | 5 | ▁▁▁▂▁▆▁▇ |
| BFIK_open_3 | numeric | 0 | 28 | 28 | 4.21 | 0.96 | 2 | 4 | 4.5 | 5 | 5 | ▁▁▂▁▁▅▁▇ |
Reliability: ωordinal [95% CI] = 0.61 [0.38;0.84].
Missing: 0.
| Index | Estimate |
|---|---|
| Omega | 0.812 |
| Omega Psych Tot | 0.3688 |
| Omega Psych H | 0.2444 |
| Omega Ordinal | 0.6077 |
| Cronbach Alpha | 0.7797 |
| Greatest Lower Bound | 0.9018 |
| Alpha Ordinal | 0.5935 |
Positive correlations: 6 out of 6 (100%)
Detailed output
#>
#> Information about this analysis:
#>
#> Dataframe: res$dat
#> Items: BFIK_consc_3, BFIK_consc_4, BFIK_consc_2R, BFIK_consc_1
#> Observations: 28
#> Positive correlations: 6 out of 6 (100%)
#>
#> Estimates assuming interval level:
#>
#> Omega (total): 0.81
#> Omega (hierarchical): 0.24
#> Revelle's omega (total): 0.37
#> Greatest Lower Bound (GLB): 0.9
#> Coefficient H: 1
#> Cronbach's alpha: 0.78
#> Confidence intervals:
#> Omega (total): [0.7, 0.92]
#> Cronbach's alpha: [0.65, 0.91]
#>
#> Estimates assuming ordinal level:
#>
#> Ordinal Omega (total): 0.61
#> Ordinal Omega (hierarch.): 0.59
#> Ordinal Cronbach's alpha: 0.59
#> Confidence intervals:
#> Ordinal Omega (total): [0.38, 0.84]
#> Ordinal Cronbach's alpha: [0.34, 0.84]
#>
#> Note: the normal point estimate and confidence interval for omega are based on the procedure suggested by Dunn, Baguley & Brunsden (2013) using the MBESS function ci.reliability, whereas the psych package point estimate was suggested in Revelle & Zinbarg (2008). See the help ('?scaleStructure') for more information.
#>
#> Eigen values: 2.473, 0.777, 0.539, 0.211
#> Loadings:
#> PC1
#> BFIK_consc_3 0.926
#> BFIK_consc_4 0.738
#> BFIK_consc_2R 0.800
#> BFIK_consc_1 0.657
#>
#> PC1
#> SS loadings 2.473
#> Proportion Var 0.618
#>
#> vars n mean sd median trimmed mad min max range skew
#> BFIK_consc_3 1 28 3.50 1.04 4 3.54 1.48 1 5 4 -0.48
#> BFIK_consc_4 2 28 3.86 0.76 4 3.88 0.00 2 5 3 -0.27
#> BFIK_consc_2R 3 28 3.18 1.31 4 3.21 1.48 1 5 4 -0.51
#> BFIK_consc_1 4 28 4.07 0.90 4 4.17 1.48 2 5 3 -0.72
#> kurtosis se
#> BFIK_consc_3 -0.50 0.20
#> BFIK_consc_4 -0.35 0.14
#> BFIK_consc_2R -1.08 0.25
#> BFIK_consc_1 -0.30 0.17
| name | data_type | missing | complete | n | mean | sd | p0 | p25 | p50 | p75 | p100 | hist |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| BFIK_consc_3 | numeric | 0 | 28 | 28 | 3.5 | 1.04 | 1 | 3 | 4 | 4 | 5 | ▁▂▁▅▁▇▁▂ |
| BFIK_consc_4 | numeric | 0 | 28 | 28 | 3.86 | 0.76 | 2 | 3 | 4 | 4 | 5 | ▁▁▃▁▁▇▁▂ |
| BFIK_consc_2R | numeric | 0 | 28 | 28 | 3.18 | 1.31 | 1 | 2 | 4 | 4 | 5 | ▃▂▁▃▁▇▁▂ |
| BFIK_consc_1 | numeric | 0 | 28 | 28 | 4.07 | 0.9 | 2 | 4 | 4 | 5 | 5 | ▁▁▂▁▁▇▁▇ |
Reliability: ωordinal [95% CI] = 0.78 [0.64;0.91].
Missing: 0.
| Index | Estimate |
|---|---|
| Omega | 0.9023 |
| Omega Psych Tot | 0.9589 |
| Omega Psych H | 0.8395 |
| Omega Ordinal | 0.775 |
| Cronbach Alpha | 0.8993 |
| Greatest Lower Bound | 0.9581 |
| Alpha Ordinal | 0.7744 |
Positive correlations: 6 out of 6 (100%)
Detailed output
#>
#> Information about this analysis:
#>
#> Dataframe: res$dat
#> Items: BFIK_extra_2, BFIK_extra_3R, BFIK_extra_4, BFIK_extra_1R
#> Observations: 28
#> Positive correlations: 6 out of 6 (100%)
#>
#> Estimates assuming interval level:
#>
#> Omega (total): 0.9
#> Omega (hierarchical): 0.84
#> Revelle's omega (total): 0.96
#> Greatest Lower Bound (GLB): 0.96
#> Coefficient H: 0.93
#> Cronbach's alpha: 0.9
#> Confidence intervals:
#> Omega (total): [0.84, 0.96]
#> Cronbach's alpha: [0.83, 0.96]
#>
#> Estimates assuming ordinal level:
#>
#> Ordinal Omega (total): 0.78
#> Ordinal Omega (hierarch.): 0.75
#> Ordinal Cronbach's alpha: 0.77
#> Confidence intervals:
#> Ordinal Omega (total): [0.64, 0.91]
#> Ordinal Cronbach's alpha: [0.64, 0.91]
#>
#> Note: the normal point estimate and confidence interval for omega are based on the procedure suggested by Dunn, Baguley & Brunsden (2013) using the MBESS function ci.reliability, whereas the psych package point estimate was suggested in Revelle & Zinbarg (2008). See the help ('?scaleStructure') for more information.
#>
#> Eigen values: 3.077, 0.527, 0.297, 0.099
#> Loadings:
#> PC1
#> BFIK_extra_2 0.806
#> BFIK_extra_3R 0.883
#> BFIK_extra_4 0.908
#> BFIK_extra_1R 0.907
#>
#> PC1
#> SS loadings 3.077
#> Proportion Var 0.769
#>
#> vars n mean sd median trimmed mad min max range skew
#> BFIK_extra_2 1 28 4.18 1.09 4 4.38 1.48 1 5 4 -1.66
#> BFIK_extra_3R 2 28 3.75 1.21 4 3.88 1.48 1 5 4 -0.76
#> BFIK_extra_4 3 28 3.86 1.11 4 3.96 1.48 1 5 4 -0.82
#> BFIK_extra_1R 4 28 3.61 1.20 4 3.67 1.48 1 5 4 -0.37
#> kurtosis se
#> BFIK_extra_2 2.40 0.21
#> BFIK_extra_3R -0.35 0.23
#> BFIK_extra_4 -0.21 0.21
#> BFIK_extra_1R -1.07 0.23
| name | data_type | missing | complete | n | mean | sd | p0 | p25 | p50 | p75 | p100 | hist |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| BFIK_extra_2 | numeric | 0 | 28 | 28 | 4.18 | 1.09 | 1 | 4 | 4 | 5 | 5 | ▁▁▁▁▁▇▁▇ |
| BFIK_extra_3R | numeric | 0 | 28 | 28 | 3.75 | 1.21 | 1 | 3 | 4 | 5 | 5 | ▂▂▁▅▁▇▁▇ |
| BFIK_extra_4 | numeric | 0 | 28 | 28 | 3.86 | 1.11 | 1 | 3 | 4 | 5 | 5 | ▁▂▁▃▁▇▁▆ |
| BFIK_extra_1R | numeric | 0 | 28 | 28 | 3.61 | 1.2 | 1 | 3 | 4 | 5 | 5 | ▁▅▁▆▁▇▁▇ |
Reliability: ωordinal [95% CI] = 0.66 [0.43;0.9].
Missing: 0.
| Index | Estimate |
|---|---|
| Omega | 0.8191 |
| Omega Psych Tot | 0.7954 |
| Omega Psych H | 0.03191 |
| Omega Ordinal | 0.665 |
| Cronbach Alpha | 0.7537 |
| Greatest Lower Bound | 0.8345 |
| Alpha Ordinal | 0.6023 |
Positive correlations: 3 out of 3 (100%)
Detailed output
#>
#> Information about this analysis:
#>
#> Dataframe: res$dat
#> Items: BFIK_neuro_2R, BFIK_neuro_3, BFIK_neuro_4
#> Observations: 28
#> Positive correlations: 3 out of 3 (100%)
#>
#> Estimates assuming interval level:
#>
#> Omega (total): 0.82
#> Omega (hierarchical): 0.03
#> Revelle's omega (total): 0.8
#> Greatest Lower Bound (GLB): 0.83
#> Coefficient H: 0.98
#> Cronbach's alpha: 0.75
#> Confidence intervals:
#> Omega (total): [0.71, 0.93]
#> Cronbach's alpha: [0.58, 0.92]
#>
#> Estimates assuming ordinal level:
#>
#> Ordinal Omega (total): 0.66
#> Ordinal Omega (hierarch.): 0.64
#> Ordinal Cronbach's alpha: 0.6
#> Confidence intervals:
#> Ordinal Omega (total): [0.43, 0.9]
#> Ordinal Cronbach's alpha: [0.34, 0.86]
#>
#> Note: the normal point estimate and confidence interval for omega are based on the procedure suggested by Dunn, Baguley & Brunsden (2013) using the MBESS function ci.reliability, whereas the psych package point estimate was suggested in Revelle & Zinbarg (2008). See the help ('?scaleStructure') for more information.
#>
#> Eigen values: 2.015, 0.723, 0.262
#> Loadings:
#> PC1
#> BFIK_neuro_2R 0.670
#> BFIK_neuro_3 0.863
#> BFIK_neuro_4 0.907
#>
#> PC1
#> SS loadings 2.015
#> Proportion Var 0.672
#>
#> vars n mean sd median trimmed mad min max range skew
#> BFIK_neuro_2R 1 28 3.11 0.88 3 3.08 1.48 2 5 3 0.12
#> BFIK_neuro_3 2 28 3.07 1.27 3 3.08 1.48 1 5 4 0.08
#> BFIK_neuro_4 3 28 2.50 1.20 2 2.50 1.48 1 4 3 0.12
#> kurtosis se
#> BFIK_neuro_2R -1.14 0.17
#> BFIK_neuro_3 -1.14 0.24
#> BFIK_neuro_4 -1.60 0.23
| name | data_type | missing | complete | n | mean | sd | p0 | p25 | p50 | p75 | p100 | hist |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| BFIK_neuro_2R | numeric | 0 | 28 | 28 | 3.11 | 0.88 | 2 | 2 | 3 | 4 | 5 | ▆▁▇▁▁▇▁▁ |
| BFIK_neuro_3 | numeric | 0 | 28 | 28 | 3.07 | 1.27 | 1 | 2 | 3 | 4 | 5 | ▃▇▁▇▁▅▁▅ |
| BFIK_neuro_4 | numeric | 0 | 28 | 28 | 2.5 | 1.2 | 1 | 1.75 | 2 | 4 | 4 | ▆▁▇▁▁▂▁▇ |
0 missing values.
| name | data_type | missing | complete | n | mean | sd | p0 | p25 | p50 | p75 | p100 | hist |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| age | integer | 0 | 28 | 28 | 29.29 | 5.97 | 20 | 25.5 | 28 | 32.75 | 43 | ▃▃▇▅▁▅▁▂ |
Where do you live?
0 missing values.
| name | label | data_type | missing | complete | n | empty | n_unique | min | max |
|---|---|---|---|---|---|---|---|---|---|
| abode | Where do you live? | character | 0 | 28 | 28 | 0 | 1 | 14 | 14 |
Reliability: ωtotal [95% CI] = 0.72 [0.56;0.89].
Missing: 0.
| Index | Estimate |
|---|---|
| Omega | 0.7248 |
| Omega Psych Tot | 0.8186 |
| Omega Psych H | 0.5611 |
| Cronbach Alpha | 0.7049 |
| Greatest Lower Bound | 0.8186 |
Positive correlations: 6 out of 6 (100%)
Detailed output
#>
#> Information about this analysis:
#>
#> Dataframe: res$dat
#> Items: normal1, normal2, normal3, normal4
#> Observations: 28
#> Positive correlations: 6 out of 6 (100%)
#>
#> Estimates assuming interval level:
#>
#> Omega (total): 0.72
#> Omega (hierarchical): 0.56
#> Revelle's omega (total): 0.82
#> Greatest Lower Bound (GLB): 0.82
#> Coefficient H: 0.75
#> Cronbach's alpha: 0.7
#> Confidence intervals:
#> Omega (total): [0.56, 0.89]
#> Cronbach's alpha: [0.52, 0.89]
#>
#> (Estimates assuming ordinal level not computed, as at least one item seems to have more than 8 levels; the highest number of distinct levels is 28 and the highest range is 7.355992. This last number needs to be lower than 9 for the polychoric function to work. If this is unexpected, you may want to check for outliers.)
#>
#> Note: the normal point estimate and confidence interval for omega are based on the procedure suggested by Dunn, Baguley & Brunsden (2013) using the MBESS function ci.reliability, whereas the psych package point estimate was suggested in Revelle & Zinbarg (2008). See the help ('?scaleStructure') for more information.
#>
#> Eigen values: 2.141, 0.84, 0.654, 0.364
#> Loadings:
#> PC1
#> normal1 0.718
#> normal2 0.786
#> normal3 0.758
#> normal4 0.659
#>
#> PC1
#> SS loadings 2.141
#> Proportion Var 0.535
#>
#> vars n mean sd median trimmed mad min max range skew
#> normal1 1 28 0.39 1.24 0.42 0.40 1.22 -2.09 2.65 4.74 -0.17
#> normal2 2 28 -0.16 1.60 -0.35 -0.18 1.48 -3.47 2.89 6.36 0.22
#> normal3 3 28 0.28 1.15 0.17 0.29 1.21 -2.27 2.48 4.75 -0.08
#> normal4 4 28 0.44 1.16 0.49 0.49 0.74 -2.73 2.51 5.24 -0.46
#> kurtosis se
#> normal1 -0.52 0.23
#> normal2 -0.62 0.30
#> normal3 -0.70 0.22
#> normal4 0.56 0.22
| name | data_type | missing | complete | n | mean | sd | p0 | p25 | p50 | p75 | p100 | hist |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| normal1 | numeric | 0 | 28 | 28 | 0.39 | 1.24 | -2.09 | -0.22 | 0.42 | 1.23 | 2.65 | ▃▁▃▆▇▇▁▃ |
| normal2 | numeric | 0 | 28 | 28 | -0.16 | 1.6 | -3.47 | -1.05 | -0.35 | 0.68 | 2.89 | ▁▂▂▇▂▅▁▃ |
| normal3 | numeric | 0 | 28 | 28 | 0.28 | 1.15 | -2.27 | -0.59 | 0.17 | 1.11 | 2.48 | ▁▃▇▃▇▅▅▂ |
| normal4 | numeric | 0 | 28 | 28 | 0.44 | 1.16 | -2.73 | 0.0046 | 0.49 | 1.03 | 2.51 | ▁▁▂▂▇▅▂▂ |
Unique ID
0 missing values.
| name | label | data_type | missing | complete | n | empty | n_unique | min | max |
|---|---|---|---|---|---|---|---|---|---|
| uniq_id | Unique ID | character | 0 | 28 | 28 | 0 | 28 | 1 | 2 |
JSON-LD metadata
The following JSON-LD can be found by search engines, if you share this codebook publicly on the web.
{
"name": "bfi",
"datePublished": "2019-02-21",
"description": "The dataset has N=28 rows and 37 columns.\n0 rows have no missing values on any column.\n\n\n## Table of variables\nThis table contains variable names, labels, their central tendencies and other attributes.\n\n|name |label |data_type |scale_item_names |missing |complete |n |empty |n_unique |count |median |min |max |mean |sd |p0 |p25 |p50 |p75 |p100 |hist |\n|:-------------|:-------------------------------|:---------|:---------------------------------------------------------|:-------|:--------|:--|:-----|:--------|:-----|:----------|:----------|:----------|:-----|:----|:-----|:------|:-----|:-----|:----|:--------|\n|session |NA |character |NA |0 |28 |28 |0 |28 |NA |NA |64 |64 |NA |NA |NA |NA |NA |NA |NA |NA |\n|created |user first opened survey |POSIXct |NA |0 |28 |28 |NA |28 |NA |2016-07-08 |2016-07-08 |2016-11-02 |NA |NA |NA |NA |NA |NA |NA |NA |\n|modified |user last edited survey |POSIXct |NA |0 |28 |28 |NA |28 |NA |2016-07-08 |2016-07-08 |2016-11-02 |NA |NA |NA |NA |NA |NA |NA |NA |\n|ended |user finished survey |POSIXct |NA |0 |28 |28 |NA |28 |NA |2016-07-08 |2016-07-08 |2016-11-02 |NA |NA |NA |NA |NA |NA |NA |NA |\n|expired |NA |logical |NA |28 |0 |28 |NA |NA |28 |NA |NA |NA |NaN |NA |NA |NA |NA |NA |NA |NA |\n|BFIK_open_2 |NA |numeric |NA |0 |28 |28 |NA |NA |NA |NA |NA |NA |4.21 |0.74 |2 |4 |4 |5 |5 |▁▁▁▁▁▇▁▅ |\n|BFIK_agree_4R |NA |numeric |NA |0 |28 |28 |NA |NA |NA |NA |NA |NA |2.93 |1.18 |1 |2 |3 |4 |5 |▂▇▁▃▁▅▁▂ |\n|BFIK_extra_2 |NA |numeric |NA |0 |28 |28 |NA |NA |NA |NA |NA |NA |4.18 |1.09 |1 |4 |4 |5 |5 |▁▁▁▁▁▇▁▇ |\n|BFIK_agree_1R |NA |numeric |NA |0 |28 |28 |NA |NA |NA |NA |NA |NA |3 |0.94 |2 |2 |3 |4 |5 |▇▁▅▁▁▆▁▁ |\n|BFIK_open_1 |NA |numeric |NA |0 |28 |28 |NA |NA |NA |NA |NA |NA |4.39 |0.83 |2 |4 |5 |5 |5 |▁▁▂▁▁▃▁▇ |\n|BFIK_neuro_2R |NA |numeric |NA |0 |28 |28 |NA |NA |NA |NA |NA |NA |3.11 |0.88 |2 |2 |3 |4 |5 |▆▁▇▁▁▇▁▁ |\n|BFIK_consc_3 |NA |numeric |NA |0 |28 |28 |NA |NA |NA |NA |NA |NA |3.5 |1.04 |1 |3 |4 |4 |5 |▁▂▁▅▁▇▁▂ |\n|BFIK_consc_4 |NA |numeric |NA |0 |28 |28 |NA |NA |NA |NA |NA |NA |3.86 |0.76 |2 |3 |4 |4 |5 |▁▁▃▁▁▇▁▂ |\n|BFIK_consc_2R |NA |numeric |NA |0 |28 |28 |NA |NA |NA |NA |NA |NA |3.18 |1.31 |1 |2 |4 |4 |5 |▃▂▁▃▁▇▁▂ |\n|BFIK_agree_3R |NA |numeric |NA |0 |28 |28 |NA |NA |NA |NA |NA |NA |3.04 |1.29 |1 |2 |3 |4 |5 |▂▇▁▃▁▇▁▃ |\n|BFIK_extra_3R |NA |numeric |NA |0 |28 |28 |NA |NA |NA |NA |NA |NA |3.75 |1.21 |1 |3 |4 |5 |5 |▂▂▁▅▁▇▁▇ |\n|BFIK_neuro_3 |NA |numeric |NA |0 |28 |28 |NA |NA |NA |NA |NA |NA |3.07 |1.27 |1 |2 |3 |4 |5 |▃▇▁▇▁▅▁▅ |\n|BFIK_neuro_4 |NA |numeric |NA |0 |28 |28 |NA |NA |NA |NA |NA |NA |2.5 |1.2 |1 |1.75 |2 |4 |4 |▆▁▇▁▁▂▁▇ |\n|BFIK_agree_2 |NA |numeric |NA |0 |28 |28 |NA |NA |NA |NA |NA |NA |3.5 |1.26 |1 |2.75 |4 |4.25 |5 |▂▅▁▅▁▇▁▆ |\n|BFIK_consc_1 |NA |numeric |NA |0 |28 |28 |NA |NA |NA |NA |NA |NA |4.07 |0.9 |2 |4 |4 |5 |5 |▁▁▂▁▁▇▁▇ |\n|BFIK_open_4 |NA |numeric |NA |0 |28 |28 |NA |NA |NA |NA |NA |NA |4.21 |0.96 |1 |4 |4 |5 |5 |▁▁▁▂▁▆▁▇ |\n|BFIK_extra_4 |NA |numeric |NA |0 |28 |28 |NA |NA |NA |NA |NA |NA |3.86 |1.11 |1 |3 |4 |5 |5 |▁▂▁▃▁▇▁▆ |\n|BFIK_extra_1R |NA |numeric |NA |0 |28 |28 |NA |NA |NA |NA |NA |NA |3.61 |1.2 |1 |3 |4 |5 |5 |▁▅▁▆▁▇▁▇ |\n|BFIK_open_3 |NA |numeric |NA |0 |28 |28 |NA |NA |NA |NA |NA |NA |4.21 |0.96 |2 |4 |4.5 |5 |5 |▁▁▂▁▁▅▁▇ |\n|BFIK_agree |aggregate of 4 BFIK_agree items |numeric |BFIK_agree_4R, BFIK_agree_1R, BFIK_agree_3R, BFIK_agree_2 |0 |28 |28 |NA |NA |NA |NA |NA |NA |3.12 |0.93 |1.5 |2.25 |3 |4 |4.75 |▂▇▂▇▃▁▅▅ |\n|BFIK_open |aggregate of 4 BFIK_open items |numeric |BFIK_open_2, BFIK_open_1, BFIK_open_4, BFIK_open_3 |0 |28 |28 |NA |NA |NA |NA |NA |NA |4.26 |0.56 |3 |3.94 |4.25 |4.75 |5 |▃▂▂▁▇▃▇▂ |\n|BFIK_consc |aggregate of 4 BFIK_consc items |numeric |BFIK_consc_3, BFIK_consc_4, BFIK_consc_2R, BFIK_consc_1 |0 |28 |28 |NA |NA |NA |NA |NA |NA |3.65 |0.79 |2 |3.12 |3.75 |4.25 |5 |▂▃▁▃▃▇▂▂ |\n|BFIK_extra |aggregate of 4 BFIK_extra items |numeric |BFIK_extra_2, BFIK_extra_3R, BFIK_extra_4, BFIK_extra_1R |0 |28 |28 |NA |NA |NA |NA |NA |NA |3.85 |1.01 |1.5 |3.25 |4.25 |4.56 |5 |▂▁▂▃▁▃▇▇ |\n|BFIK_neuro |aggregate of 3 BFIK_neuro items |numeric |BFIK_neuro_2R, BFIK_neuro_3, BFIK_neuro_4 |0 |28 |28 |NA |NA |NA |NA |NA |NA |2.89 |0.93 |1.33 |2 |2.83 |3.42 |4.33 |▅▅▂▅▃▅▁▇ |\n|age |NA |integer |NA |0 |28 |28 |NA |NA |NA |NA |NA |NA |29.29 |5.97 |20 |25.5 |28 |32.75 |43 |▃▃▇▅▁▅▁▂ |\n|abode |Where do you live? |character |NA |0 |28 |28 |0 |1 |NA |NA |14 |14 |NA |NA |NA |NA |NA |NA |NA |NA |\n|normal1 |NA |numeric |NA |0 |28 |28 |NA |NA |NA |NA |NA |NA |0.39 |1.24 |-2.09 |-0.22 |0.42 |1.23 |2.65 |▃▁▃▆▇▇▁▃ |\n|normal2 |NA |numeric |NA |0 |28 |28 |NA |NA |NA |NA |NA |NA |-0.16 |1.6 |-3.47 |-1.05 |-0.35 |0.68 |2.89 |▁▂▂▇▂▅▁▃ |\n|normal3 |NA |numeric |NA |0 |28 |28 |NA |NA |NA |NA |NA |NA |0.28 |1.15 |-2.27 |-0.59 |0.17 |1.11 |2.48 |▁▃▇▃▇▅▅▂ |\n|normal4 |NA |numeric |NA |0 |28 |28 |NA |NA |NA |NA |NA |NA |0.44 |1.16 |-2.73 |0.0046 |0.49 |1.03 |2.51 |▁▁▂▂▇▅▂▂ |\n|normal |aggregate of 4 normal items |numeric |normal1, normal2, normal3, normal4 |0 |28 |28 |NA |NA |NA |NA |NA |NA |0.24 |0.95 |-1.74 |-0.44 |0.35 |0.78 |2.25 |▃▁▆▃▇▃▃▁ |\n|uniq_id |Unique ID |character |NA |0 |28 |28 |0 |28 |NA |NA |1 |2 |NA |NA |NA |NA |NA |NA |NA |NA |\n\n### Note\nThis dataset was automatically described using the [codebook R package](https://rubenarslan.github.io/codebook/) (version 0.7.6.9000).",
"keywords": ["session", "created", "modified", "ended", "expired", "BFIK_open_2", "BFIK_agree_4R", "BFIK_extra_2", "BFIK_agree_1R", "BFIK_open_1", "BFIK_neuro_2R", "BFIK_consc_3", "BFIK_consc_4", "BFIK_consc_2R", "BFIK_agree_3R", "BFIK_extra_3R", "BFIK_neuro_3", "BFIK_neuro_4", "BFIK_agree_2", "BFIK_consc_1", "BFIK_open_4", "BFIK_extra_4", "BFIK_extra_1R", "BFIK_open_3", "BFIK_agree", "BFIK_open", "BFIK_consc", "BFIK_extra", "BFIK_neuro", "age", "abode", "normal1", "normal2", "normal3", "normal4", "normal", "uniq_id"],
"@context": "http://schema.org/",
"@type": "Dataset",
"variableMeasured": [
{
"name": "session",
"@type": "propertyValue"
},
{
"name": "created",
"description": "user first opened survey",
"@type": "propertyValue"
},
{
"name": "modified",
"description": "user last edited survey",
"@type": "propertyValue"
},
{
"name": "ended",
"description": "user finished survey",
"@type": "propertyValue"
},
{
"name": "expired",
"@type": "propertyValue"
},
{
"name": "BFIK_open_2",
"@type": "propertyValue"
},
{
"name": "BFIK_agree_4R",
"@type": "propertyValue"
},
{
"name": "BFIK_extra_2",
"@type": "propertyValue"
},
{
"name": "BFIK_agree_1R",
"@type": "propertyValue"
},
{
"name": "BFIK_open_1",
"@type": "propertyValue"
},
{
"name": "BFIK_neuro_2R",
"@type": "propertyValue"
},
{
"name": "BFIK_consc_3",
"@type": "propertyValue"
},
{
"name": "BFIK_consc_4",
"@type": "propertyValue"
},
{
"name": "BFIK_consc_2R",
"@type": "propertyValue"
},
{
"name": "BFIK_agree_3R",
"@type": "propertyValue"
},
{
"name": "BFIK_extra_3R",
"@type": "propertyValue"
},
{
"name": "BFIK_neuro_3",
"@type": "propertyValue"
},
{
"name": "BFIK_neuro_4",
"@type": "propertyValue"
},
{
"name": "BFIK_agree_2",
"@type": "propertyValue"
},
{
"name": "BFIK_consc_1",
"@type": "propertyValue"
},
{
"name": "BFIK_open_4",
"@type": "propertyValue"
},
{
"name": "BFIK_extra_4",
"@type": "propertyValue"
},
{
"name": "BFIK_extra_1R",
"@type": "propertyValue"
},
{
"name": "BFIK_open_3",
"@type": "propertyValue"
},
{
"name": "BFIK_agree",
"description": "aggregate of 4 BFIK_agree items",
"@type": "propertyValue"
},
{
"name": "BFIK_open",
"description": "aggregate of 4 BFIK_open items",
"@type": "propertyValue"
},
{
"name": "BFIK_consc",
"description": "aggregate of 4 BFIK_consc items",
"@type": "propertyValue"
},
{
"name": "BFIK_extra",
"description": "aggregate of 4 BFIK_extra items",
"@type": "propertyValue"
},
{
"name": "BFIK_neuro",
"description": "aggregate of 3 BFIK_neuro items",
"@type": "propertyValue"
},
{
"name": "age",
"@type": "propertyValue"
},
{
"name": "abode",
"description": "Where do you live?",
"@type": "propertyValue"
},
{
"name": "normal1",
"@type": "propertyValue"
},
{
"name": "normal2",
"@type": "propertyValue"
},
{
"name": "normal3",
"@type": "propertyValue"
},
{
"name": "normal4",
"@type": "propertyValue"
},
{
"name": "normal",
"description": "aggregate of 4 normal items",
"@type": "propertyValue"
},
{
"name": "uniq_id",
"description": "Unique ID",
"@type": "propertyValue"
}
]
}`