PROMAX {EFA.dimensions}

R Documentation

promax rotation

Description

promax rotation

Usage

PROMAX(loadings, ppower, verbose)

Arguments

loadings	A loading matrix.
ppower	The exponent for the promax target matrix. 'ppower' must be 1 or greater. '4' is a conventional value.
verbose	Should detailed results be displayed in console? TRUE (default) or FALSE

Details

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

Value

A list with the following elements:

loadingsNOROT	The unrotated loadings
pattern	The pattern matrix (for promax rotation)
structure	The structure matrix (for promax rotation)
phi	The correlations between the factors (for promax rotation)
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)
PROMAX(PCAoutput$loadingsNOROT, ppower = 4, verbose=TRUE)

# Rosenberg Self-Esteem scale items
PCAoutput <- PCA(data_RSE, corkind='polychoric', Nfactors = 2, rotate='none', verbose=TRUE)
PROMAX(PCAoutput$loadingsNOROT, ppower = 4, verbose=TRUE)

# NEO-PI-R scales
PCAoutput <- PCA(data_NEOPIR, corkind='pearson', Nfactors = 5, rotate='none', verbose=TRUE)
PROMAX(PCAoutput$loadingsNOROT, ppower = 4, verbose=TRUE)

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