getSRMR.Sigma

Computes SRMR given the model-implied and the observed (or population) covariance matrix,
using the Hu &amp; Bentler approach to standardization.

Provides a-priori, post-hoc, and compromise power-analyses
for structural equation models (SEM).

Morten Moshagen

semPower

Power Analyses for SEM

Martina Bader

getSRMR.Sigma function

<dl><dt>SigmaHat</dt>
<dd>model implied covariance matrix</dd>
<dt>S</dt>
<dd>observed (or population) covariance matrix</dd>
<dt>muHat</dt>
<dd>model implied mean vector</dd>
<dt>mu</dt>
<dd>observed (or population) mean vector</dd></dl>

Arguments

getSRMR.Sigma — getSRMR.Sigma

<dl>

<dt>SigmaHat</dt>
<dd>model implied covariance matrix</dd>


<dt>S</dt>
<dd>observed (or population) covariance matrix</dd>


<dt>muHat</dt>
<dd>model implied mean vector</dd>


<dt>mu</dt>
<dd>observed (or population) mean vector</dd>

</dl>

getSRMR.Sigma: getSRMR.Sigma

Description

Usage

Value

Arguments