FA: Factor Analysis

In Rkabacoff/factorAnalysis: Principal Components, Factor Analysis, and Clustering Tools

Factor Analysis

Description

FA performs common factor analysis

Usage

FA(data, nfactors = NULL, rotate = "none", fm = "pa", digits = 2, ...)

Arguments

data	a data frame or correlation matrix.
nfactors	nuber of factors to extract.
rotate	factor rotation to perform.
fm	type of factor extraction.
digits	number of digits to retain.
...	parameters passed to the psych::fa function.

Details

The FA function is a wrapper for the psych:fa function. Factor extractions include principal axis (pa) and maximum likelihood (ml), among others. Factor rotations include none, varimax, and promax.

Value

returns a list with 5 components:

call	the call
loadings	factor pattern
variance	variance accounted for
Structure	structure matrix
phi	factor intercorrelations for oblique rotations
scores	factor scores if factors are extracted from a data frame

Examples

fit.fa <- FA(Harman74.cor$cov, nfactors=4, rotate="varimax")

Rkabacoff/factorAnalysis documentation built on March 21, 2022, 3:15 p.m.