Fits the Rasch PCM model using eRm, and conducts a PCA of residuals to get eigenvalues using psych::pca() and reports the top 5 values. Proportion of explained variance is calculated using stats::prcomp().

Note from ?psych::pca: The eigenvectors are rescaled by the sqrt of the eigenvalues to produce the component loadings more typical in factor analysis.

Usage

RIpcmPCA(dfin, output = "table", fontsize = 15)

Arguments

dfin

Dataframe with item data only

output

Defaults to "table", optional "dataframe"

fontsize

Set font size for table

Details

See Chou & Wang (2010, DOI: 10.1177/0013164410379322) for a simulation study testing PCA eigenvalues across multiple conditions.