EKC: Empirical Kaiser Criterion (EKC)

In Rnest: Next Eigenvalue Sufficiency Test

Empirical Kaiser Criterion (EKC)

Description

Empirical Kaiser Criterion (EKC)

Usage

EKC(.data = NULL, n = NULL, nv = NULL, lowest.eig = 1, ...)

Arguments

.data	a data frame, a numeric matrix, covariance matrix or correlation matrix from which to determine the number of factors.
n	the number of cases (subjects, participants, or units) if a covariance matrix is supplied in .data.
nv	the number of variables if the critical values are required.
lowest.eig	minimal eigenvalues to retain. Default is Kaiser's suggestion of 1.
...	further argument for cor_nest().

Value

The number of factors to retain or the crititical eigenvalues.

References

Braeken, J., & van Assen, M. A. L. M. (2017). An empirical Kaiser criterion. Psychological Methods, 22(3), 450–466. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1037/met0000074")}

Examples

EKC(ex_4factors_corr, n = 42)

Rnest documentation built on April 3, 2025, 5:31 p.m.