faStandardize: Standardize the Unrotated Factor Loadings

Description Usage Arguments Value References See Also

View source: R/faStandardize.R

Description

This function standardizes the unrotated factor loadings using two methods: Kaiser's normalization and Cureton-Mulaik standardization.

Usage

1
faStandardize(method, lambda)

Arguments

method

(Character) The method used for standardization. There are three option: "none", "Kaiser", and "CM".

  • "none": No standardization is conducted on the unrotated factor loadings matrix

  • "Kaiser": The rows of the unrotated factor loadings matrix are rescaled to have unit-lengths.

  • "CM": Apply the Cureton-Mulaik standardization to the unrotated factor loadings matrix.

lambda

(Matrix) The unrotated factor loadings matrix (or data frame).

Value

The resulting output can be used to standardize the factor loadings as well as providing the inverse matrix used to unstandardize the factor loadings after rotating the factor solution.

References

Browne, M. W. (2001). An overview of analytic rotation in exploratory factor analysis. Multivariate Behavioral Research, 36(1), 111-150.

Cureton, E. E., & Mulaik, S. A. (1975). The weighted varimax rotation and the promax rotation. Psychometrika, 40(2), 183-195.

See Also

Other Factor Analysis Routines: BiFAD(), Box26, GenerateBoxData(), Ledermann(), SLi(), SchmidLeiman(), faAlign(), faEKC(), faIB(), faLocalMin(), faMB(), faMain(), faScores(), faSort(), faX(), fals(), fapa(), fareg(), fsIndeterminacy(), orderFactors(), print.faMB(), print.faMain(), promaxQ(), summary.faMB(), summary.faMain()


fungible documentation built on Sept. 29, 2021, 1:06 a.m.