.hyperplane_count

Hyperplane count is the number of loadings with absolute value smaller than a
user-specified cutoff.

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

Silvia Steiner

William Revelle

Max Auerswald

Morten Moshagen

John Ruscio

Brendan Roche

Urbano Lorenzo-Seva

David Navarro-Gonzalez

Johan Braeken

Andreas Soteriades

.hyperplane_count function

<dl><dt>L</dt>
<dd>Numeric loading matrix.</dd>
<dt>cutoff</dt>
<dd>Numeric scalar. Loadings with <code>abs(L) &lt; cutoff</code> are counted as
being in the hyperplane.</dd></dl>

Arguments

Count near-zero loadings — .hyperplane_count

<dl>

<dt>L</dt>
<dd>Numeric loading matrix.</dd>


<dt>cutoff</dt>
<dd>Numeric scalar. Loadings with <code>abs(L) &lt; cutoff</code> are counted as
being in the hyperplane.</dd>

</dl>

Count near-zero loadings

.hyperplane_count: Count near-zero loadings

Description

Usage

Value

Arguments