<a href="https://lifecycle.r-lib.org/articles/stages.html#superseded"><img src="figures/lifecycle-superseded.svg?package=EFAtools&version=1.1.0" alt="[Superseded]"></a>
<code>SMT()</code> has been superseded by <code>efa_smt()</code>, which is the recommended interface
going forward. It remains available and unchanged so existing code keeps working.

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

SMT function

<dl><dt>x</dt>
<dd>data.frame or matrix. Dataframe or matrix of raw data or matrix with
correlations.</dd>
<dt>N</dt>
<dd>numeric. The number of observations. Needs only be specified if a
correlation matrix is used. Must be larger than the number of variables.</dd>
<dt>use</dt>
<dd>character. Passed to <code><a href="/link/stats%3A%3Acor()?package=EFAtools&version=1.1.0" data-mini-rdoc="EFAtools::stats::cor()">stats::cor()</a></code> if raw
data is given as input. Default is "pairwise.complete.obs".</dd>
<dt>cor_method</dt>
<dd>character. One of <code>"pearson"</code>, <code>"spearman"</code>, or <code>"kendall"</code>,
passed to <code><a href="/link/stats%3A%3Acor()?package=EFAtools&version=1.1.0" data-mini-rdoc="EFAtools::stats::cor()">stats::cor()</a></code>. <code>"poly"</code> and <code>"tetra"</code> are not supported because
<code>SMT</code> rests on a normal-theory chi-square test that is not valid for
polychoric / tetrachoric correlations.
Default is <code>"pearson"</code>.</dd></dl>

Arguments

<a href='https://lifecycle.r-lib.org/articles/stages.html#superseded'><img src='figures/lifecycle-superseded.svg' alt='[Superseded]' /></a>
<code>SMT()</code> has been superseded by <code>efa_smt()</code>, which is the recommended interface
going forward. It remains available and unchanged so existing code keeps working.

Sequential model tests — SMT

<dl>

<dt>x</dt>
<dd>data.frame or matrix. Dataframe or matrix of raw data or matrix with
correlations.</dd>


<dt>N</dt>
<dd>numeric. The number of observations. Needs only be specified if a
correlation matrix is used. Must be larger than the number of variables.</dd>


<dt>use</dt>
<dd>character. Passed to <code><a href='https://rdrr.io/r/stats/cor.html'>stats::cor()</a></code> if raw
data is given as input. Default is "pairwise.complete.obs".</dd>


<dt>cor_method</dt>
<dd>character. One of <code>"pearson"</code>, <code>"spearman"</code>, or <code>"kendall"</code>,
passed to <code><a href='https://rdrr.io/r/stats/cor.html'>stats::cor()</a></code>. <code>"poly"</code> and <code>"tetra"</code> are not supported because
<code>SMT</code> rests on a normal-theory chi-square test that is not valid for
polychoric / tetrachoric correlations.
Default is <code>"pearson"</code>.</dd>

</dl>

SMT: Sequential model tests

Description

Usage

Value

Arguments

See Also