check_itemscale: Describe Properties of Item Scales

Description Usage Arguments Details Value Note References Examples

View source: R/check_itemscale.R

Description

Compute various measures of internal consistencies applied to (sub)scales, which items were extracted using parameters::principal_components().

Usage

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Arguments

x

An object of class parameters_pca, as returned by parameters::principal_components().

Details

check_itemscale() calculates various measures of internal consistencies, such as Cronbach's alpha, item difficulty or discrimination etc. on subscales which were built from several items. Subscales are retrieved from the results of parameters::principal_components(), i.e. based on how many components were extracted from the PCA, check_itemscale() retrieves those variables that belong to a component and calculates the above mentioned measures.

Value

A list of data frames, with related measures of internal consistencies of each subscale.

Note

References

Examples

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# data generation from '?prcomp', slightly modified
C <- chol(S <- toeplitz(.9^(0:15)))
set.seed(17)
X <- matrix(rnorm(1600), 100, 16)
Z <- X %*% C
if (require("parameters") && require("psych")) {
  pca <- principal_components(as.data.frame(Z), rotation = "varimax", n = 3)
  pca
  check_itemscale(pca)
}

Example output

Loading required package: parameters
Loading required package: psych
# Description of (Sub-)Scales

Component 1

Item | Missings |  Mean |   SD | Skewness | Difficulty | Discrimination | alpha if deleted
------------------------------------------------------------------------------------------
V1   |    0.00% | -0.02 | 1.06 |    -0.49 |      -0.01 |           0.80 |             0.96
V2   |    0.00% | -0.05 | 1.05 |    -0.29 |      -0.02 |           0.90 |             0.95
V3   |    0.00% |  0.00 | 1.10 |    -0.77 |       0.00 |           0.94 |             0.95
V4   |    0.00% | -0.00 | 1.10 |    -0.82 |       0.00 |           0.92 |             0.95
V5   |    0.00% | -0.07 | 1.09 |    -0.29 |      -0.03 |           0.90 |             0.95
V6   |    0.00% | -0.04 | 1.13 |    -0.27 |      -0.01 |           0.83 |             0.96

Mean inter-item-correlation = 0.813  Cronbach's alpha = 0.963


Component 2

Item | Missings |  Mean |   SD | Skewness | Difficulty | Discrimination | alpha if deleted
------------------------------------------------------------------------------------------
V7   |    0.00% | -0.01 | 1.07 |     0.01 |       0.00 |           0.87 |             0.97
V8   |    0.00% |  0.02 | 0.96 |     0.23 |       0.01 |           0.89 |             0.96
V9   |    0.00% |  0.04 | 0.98 |     0.37 |       0.01 |           0.93 |             0.96
V10  |    0.00% |  0.08 | 1.00 |     0.18 |       0.03 |           0.93 |             0.96
V11  |    0.00% |  0.02 | 1.03 |     0.18 |       0.01 |           0.92 |             0.96
V12  |    0.00% | -0.00 | 1.04 |     0.27 |       0.00 |           0.84 |             0.97

Mean inter-item-correlation = 0.840  Cronbach's alpha = 0.969


Component 3

Item | Missings |  Mean |   SD | Skewness | Difficulty | Discrimination | alpha if deleted
------------------------------------------------------------------------------------------
V13  |    0.00% |  0.04 | 0.95 |     0.10 |       0.02 |           0.81 |             0.95
V14  |    0.00% | -0.02 | 0.96 |     0.24 |      -0.01 |           0.93 |             0.91
V15  |    0.00% | -0.03 | 0.94 |     0.41 |      -0.01 |           0.92 |             0.91
V16  |    0.00% |  0.03 | 0.96 |     0.28 |       0.01 |           0.82 |             0.94

Mean inter-item-correlation = 0.811  Cronbach's alpha = 0.945

performance documentation built on Oct. 1, 2021, 5:08 p.m.