getF

Computes the minimum of the ML-fit-function from known fit indices.

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

Morten Moshagen

semPower

Power Analyses for SEM

Martina Bader

getF function

<dl><dt>effect</dt>
<dd>magnitude of effect</dd>
<dt>effect.measure</dt>
<dd>measure of effect, one of <code>'fmin'</code>, <code>'rmsea'</code>, <code>'agfi'</code>, <code>'gfi'</code>, <code>'mc'</code></dd>
<dt>df</dt>
<dd>model degrees of freedom</dd>
<dt>p</dt>
<dd>number of observed variables</dd>
<dt>SigmaHat</dt>
<dd>model implied covariance matrix</dd>
<dt>Sigma</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>
<dt>fittingFunction</dt>
<dd>one of <code>ML</code> (default), <code>WLS</code>, <code>DWLS</code>, <code>ULS</code></dd></dl>

Arguments

getF — getF

<dl>

<dt>effect</dt>
<dd>magnitude of effect</dd>


<dt>effect.measure</dt>
<dd>measure of effect, one of <code>'fmin'</code>, <code>'rmsea'</code>, <code>'agfi'</code>, <code>'gfi'</code>, <code>'mc'</code></dd>


<dt>df</dt>
<dd>model degrees of freedom</dd>


<dt>p</dt>
<dd>number of observed variables</dd>


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


<dt>Sigma</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>


<dt>fittingFunction</dt>
<dd>one of <code>ML</code> (default), <code>WLS</code>, <code>DWLS</code>, <code>ULS</code></dd>

</dl>

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getF: getF

Description

Usage

Value

Arguments