VARIMAX {EFA.dimensions}

R Documentation

varimax rotation

Description

varimax rotation

Usage

VARIMAX(loadings, normalize = TRUE, verbose)

Arguments

loadings	A loading matrix.
normalize	Should Kaiser normalization be performed? If so the rows of x are re-scaled to unit length before rotation, and scaled back afterwards. Default = TRUE.
verbose	Should detailed results be displayed in console? TRUE (default) or FALSE

Details

This function uses the R built-in varimax function and provides additional output.

Value

A list with the following elements:

loadingsNOROT	The unrotated loadings
loadingsV	The varimax-rotated loadings
rotmatV	The rotation matrix
cormat_reproduced	The reproduced correlation matrix, based on the rotated loadings

Author(s)

Brian P. O'Connor

Examples

# the Harman (1967) correlation matrix
PCAoutput <- PCA(data_Harman, Nfactors = 2, Ncases=305, rotate='none', verbose=TRUE)
VARIMAX(PCAoutput$loadingsNOROT, verbose=TRUE)

# Rosenberg Self-Esteem scale items
PCAoutput <- PCA(data_RSE, corkind='polychoric', Nfactors = 2, rotate='none', verbose=TRUE)
VARIMAX(PCAoutput$loadingsNOROT, verbose=TRUE)

# NEO-PI-R scales
PCAoutput <- PCA(data_NEOPIR, Nfactors = 5, rotate='none', verbose=TRUE)
VARIMAX(PCAoutput$loadingsNOROT, verbose=TRUE)

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