.factor_corres

Compute number of non-matching indicator-to-factor correspondences

Provides functions to perform exploratory factor analysis (EFA) procedures and compare their solutions. The goal is to provide state-of-the-art factor retention methods and a high degree of flexibility in the EFA procedures. This way, for example, implementations from R 'psych' and 'SPSS' can be compared. Moreover, functions for Schmid-Leiman transformation and the computation of omegas are provided. To speed up the analyses, some of the iterative procedures, like principal axis factoring (PAF), are implemented in C++.

Markus Steiner

EFAtools

Fast and Flexible Implementations of Exploratory Factor Analysis
Tools

.factor_corres function

<dl><dt>x</dt>
<dd>numeric matrix. A matrix of pattern coefficients.</dd>
<dt>y</dt>
<dd>numeric matrix. A second matrix of coefficients.</dd>
<dt>thresh</dt>
<dd>numeric. The threshold to classify a pattern coefficient as substantial.</dd></dl>

Arguments

Compute number of non-matching indicator-to-factor correspondences — .factor_corres

<dl>

<dt>x</dt>
<dd>numeric matrix. A matrix of pattern coefficients.</dd>


<dt>y</dt>
<dd>numeric matrix. A second matrix of coefficients.</dd>


<dt>thresh</dt>
<dd>numeric. The threshold to classify a pattern coefficient as substantial.</dd>

</dl>

.factor_corres: Compute number of non-matching indicator-to-factor correspondences

Description

Usage

Arguments