print.KGC

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

print.KGC function

<dl><dt>x</dt>
<dd>a list of class KGC. Output from KGC function.</dd>
<dt>plot</dt>
<dd>logical. Whether to plot the results.</dd>
<dt>...</dt>
<dd>Further arguments for print.</dd></dl>

Arguments

Print function for KGC objects — print.KGC

<dl>

<dt>x</dt>
<dd>a list of class KGC. Output from KGC function.</dd>


<dt>plot</dt>
<dd>logical. Whether to plot the results.</dd>


<dt>...</dt>
<dd>Further arguments for print.</dd>

</dl>

print.KGC: Print function for KGC objects

Description

Usage

Arguments

Examples