.tucker_congruence

Compute the Tucker congruence matrix between the columns of two loading
matrices.

internal

Provides a complete workflow for exploratory factor analysis
(EFA). It covers data screening and factorability checks, a suite of
factor retention criteria for choosing the number of factors, and factor
extraction by principal axis factoring, maximum likelihood, unweighted
least squares, or diagonally weighted least squares from Pearson,
Spearman, Kendall, polychoric, tetrachoric, or two-stage
full-information maximum likelihood correlations. A built-in rotation
engine offers a range of orthogonal and oblique rotations, and standard
errors for loadings and related quantities can be obtained by analytic,
robust, or bootstrap methods. Further tools support model averaging
across analytic choices, multigroup EFA with factor congruence, EFA on
multiply imputed data, Schmid-Leiman transformation, reliability
coefficients (including McDonald's omegas), factor score estimation,
data simulation, and power analysis. Computationally intensive
procedures are implemented in 'C++' for speed.

Markus Steiner

EFAtools

Fast and Flexible Implementations of Exploratory Factor Analysis
Tools

.tucker_congruence function

<dl><dt>L1</dt>
<dd>Numeric matrix.</dd>
<dt>L2</dt>
<dd>Numeric matrix with the same dimensions as <code>L1</code>.</dd></dl>

Arguments

Tucker congruence between factors — .tucker_congruence

<dl>

<dt>L1</dt>
<dd>Numeric matrix.</dd>


<dt>L2</dt>
<dd>Numeric matrix with the same dimensions as <code>L1</code>.</dd>

</dl>

.tucker_congruence: Tucker congruence between factors

Description

Usage

Value

Arguments

References