get_std_loadings

Extract standardized factor loadings from lavaan object

Provides functions to identify plausible and replicable factor
structures for a set of variables via k-fold cross validation. The process
combines the exploratory and confirmatory factor analytic approach to scale
development (Flora & Flake, 2017) <doi:10.1037/cbs0000069> with a cross validation
technique that maximizes the available data (Hastie, Tibshirani, & Friedman, 2009)
<isbn:978-0-387-21606-5>. Also available are functions to determine k by drawing
on power analytic techniques for covariance structures (MacCallum, Browne, &
Sugawara, 1996) <doi:10.1037/1082-989X.1.2.130>, generate model syntax, and
summarize results in a report.

Kyle Nickodem

K-Fold Cross Validation for Factor Analysis

get_std_loadings function

<dl><dt>object</dt>
<dd>a <code>lavaan</code> object</dd>
<dt>type</dt>
<dd>standardize on the latent variables (<code>"std.lv"</code>),
latent and observed variables (<code>"std.all"</code>, default), or latent and observed variables
but not exogenous variables (<code>"std.nox"</code>)? See <code>standardizedSolution</code>.</dd>
<dt>df</dt>
<dd>should loadings be returned as a <code>matrix</code> (default) or <code>data.frame</code>?</dd></dl>

Arguments

Standardized factor loadings matrix — get_std_loadings

<dl>

<dt>object</dt>
<dd>a <code>lavaan</code> object</dd>


<dt>type</dt>
<dd>standardize on the latent variables (<code>"std.lv"</code>),
latent and observed variables (<code>"std.all"</code>, default), or latent and observed variables
but not exogenous variables (<code>"std.nox"</code>)? See <code>standardizedSolution</code>.</dd>


<dt>df</dt>
<dd>should loadings be returned as a <code>matrix</code> (default) or <code>data.frame</code>?</dd>

</dl>

get_std_loadings: Standardized factor loadings matrix

Description

Usage

Value

Arguments

Examples