EFA.dimensions (version 0.1.7.2)

PROMAX: 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

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)

eigenvar

Eigenvalues and factor proportions of variance (for promax rotation)

cormat_reproduced

The reproduced correlation matrix, based on the rotated loadings

Details

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

Examples

# NOT RUN {
# 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)
# }