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)


[Package EFA.dimensions version 0.1.7.4 Index]