plot

plot.Hull

plot.CD

plot.PA

plot.EKC

plot.KGC

plot.EFAkmeans

plot.EFAhclust

plot.NN

plot.FF

plot.CDF

plot.EFAvote

plot.EFAscreet

plot.MAP

plot.STOC

These `plot` methods for different results, including:<ul>
<li>Hull plot for <code>Hull</code> results.</li>
<li>Comparison Data plot for <code>CD</code> results.</li>
<li>Parallel Analysis plot for <code>PA</code> results.</li>
<li>Empirical Kaiser Criterion for <code>EKC</code> results.</li>
<li>Kaiser-Guttman Criterion for <code>KGC</code> results.</li>
<li>K-means plot for <code>EFAkmeans</code> results.</li>
<li>Hierarchical Clustering plot for <code>EFAhclust</code> results.</li>
<li>pre-trained Neural Networks plot for <code>NN</code> results.</li>
<li>Factor Forest for <code>FF</code> results.</li>
<li>Comparison Data Forest plot for <code>CDF</code> results.</li>
<li>Voting Method plot for <code>EFAvote</code> results.</li>
<li>Scree Plot for <code>EFAscreet</code> results.</li>
<li>Minimum Average Partial Test plot for <code>MAP</code> results.</li>
<li>Scree Test Optimal Coordinate plot for <code>STOC</code> results.</li>
</ul>

Provides a collection of standard factor retention methods in Exploratory Factor
Analysis (EFA), making it easier to determine the number of factors. Traditional
methods such as the scree plot by Cattell (1966) <doi:10.1207/s15327906mbr0102_10>,
Kaiser-Guttman Criterion (KGC) by Guttman (1954) <doi:10.1007/BF02289162> and
Kaiser (1960) <doi:10.1177/001316446002000116>, and flexible Parallel Analysis
(PA) by Horn (1965) <doi:10.1007/BF02289447> based on eigenvalues form PCA or EFA
are readily available. This package also implements several newer methods, such as
the Empirical Kaiser Criterion (EKC) by Braeken and van Assen (2017)
<doi:10.1037/met0000074>, Comparison Data (CD) by Ruscio and Roche (2012)
<doi:10.1037/a0025697>, and Hull method by Lorenzo-Seva et al. (2011)
<doi:10.1080/00273171.2011.564527>, as well as some AI-based methods like
Comparison Data Forest (CDF) by Goretzko and Ruscio (2024)
<doi:10.3758/s13428-023-02122-4> and Factor Forest (FF) by Goretzko and Buhner
(2020) <doi:10.1037/met0000262>. Additionally, it includes a deep neural network
(DNN) trained on large-scale datasets that can efficiently and reliably determine
the number of factors.

Haijiang Qin

EFAfactors

Determining the Number of Factors in Exploratory Factor Analysis

Lei Guo

plot function

<dl><dt>x</dt>
<dd>An object of class <code>Hull</code>, <code>CD</code>, <code>PA</code>, <code>EKC</code>,
<code>KGC</code>, <code>EFAkmeans</code>, <code>EFAhclust</code>, <code>NN</code>, <code>FF</code>,
<code>CDF</code>, <code>EFAvote</code>, <code>EFAscreet</code>, <code>MAP</code>, or <code>STOC</code>.</dd>
<dt>...</dt>
<dd>Additional arguments passed to the plotting functions.</dd></dl>

Arguments

<ul>
<li><code>plot(Hull)</code>: Plot method for Hull objects</li>
<li><code>plot(CD)</code>: Plot method for CD objects</li>
<li><code>plot(PA)</code>: Plot method for PA objects</li>
<li><code>plot(EKC)</code>: Plot method for EKC objects</li>
<li><code>plot(KGC)</code>: Plot method for KGC objects</li>
<li><code>plot(EFAkmeans)</code>: Plot method for EFAkmeans objects</li>
<li><code>plot(EFAhclust)</code>: Plot method for EFAhclust objects</li>
<li><code>plot(NN)</code>: Plot method for NN objects</li>
<li><code>plot(FF)</code>: Plot method for FF objects</li>
<li><code>plot(CDF)</code>: Plot method for CDF objects</li>
<li><code>plot(EFAvote)</code>: Plot method for EFAvote objects</li>
<li><code>plot(EFAscreet)</code>: Plot method for EFAscreet objects</li>
<li><code>plot(MAP)</code>: Plot method for MAP objects</li>
<li><code>plot(STOC)</code>: Plot method for STOC objects</li>
</ul>

Methods (by class)

Plot Methods — plot

<dl>

<dt>x</dt>
<dd>An object of class <code>Hull</code>, <code>CD</code>, <code>PA</code>, <code>EKC</code>,
<code>KGC</code>, <code>EFAkmeans</code>, <code>EFAhclust</code>, <code>NN</code>, <code>FF</code>,
<code>CDF</code>, <code>EFAvote</code>, <code>EFAscreet</code>, <code>MAP</code>, or <code>STOC</code>.</dd>


<dt>...</dt>
<dd>Additional arguments passed to the plotting functions.</dd>

</dl>

Plot Methods

plot: Plot Methods

Description

Usage

Value

Arguments

Methods (by class)

See Also