EFA.dimensions (version 0.1.6)

ROOTFIT: Factor fit coefficients

Description

A variety of fit coefficients for the possible N-factor solutions in exploratory factor analysis

Usage

ROOTFIT(data, corkind, Ncases, extract, verbose)

Arguments

data

An all-numeric dataframe where the rows are cases & the columns are the variables, or a correlation matrix with ones on the diagonal.The function internally determines whether the data are a correlation matrix.

corkind

The kind of correlation matrix to be used if data is not a correlation matrix. The options are 'pearson', 'kendall', 'spearman', and 'polychoric'. Required only if the entered data is not a correlation matrix.

Ncases

The number of cases upon which a correlation matrix is based. Required only if data is a correlation matrix.

extract

The factor extraction method. The options are: 'PAF' for principal axis / common factor analysis; 'PCA' for principal components analysis. 'ML' for maximum likelihood estimation.

verbose

Should detailed results be displayed in console? The options are: TRUE (default) or FALSE.

Value

A list with eigenvalues & fit coefficients.

Examples

# NOT RUN {
# RSE data
ROOTFIT(data_RSE, corkind='pearson', extract='ML')
ROOTFIT(data_RSE, corkind='pearson', extract='PCA')

# }
# NOT RUN {
# NEO-PI-R data
ROOTFIT(data_NEOPIR, corkind='pearson', extract='ML')
ROOTFIT(data_NEOPIR, corkind='pearson', extract='PCA')
# }