fit_indices

chisq

rmsea

Uses both ridge and lasso penalties (and extensions) to penalize
specific parameters in structural equation models. The package offers additional
cost functions, cross validation, and other extensions beyond traditional structural
equation models. Also contains a function to perform exploratory mediation (XMed).

Ross Jacobucci

regsem

Regularized Structural Equation Modeling

Kevin Grimm

Andreas Brandmaier

Sarfaraz Serang

Rogier Kievit

Florian Scharf

Xiaobei Li

Ai Ye

fit_indices function

<dl><dt>model</dt>
<dd>regsem model object.</dd>
<dt>CV</dt>
<dd>cross-validation. Note that this requires splitting the dataset
into a training and test set prior to running the model. The
model should be run on the training set, with the test set
held out and then passed to CovMat=.</dd>
<dt>CovMat</dt>
<dd>If CV=T then test covariance matrix must be supplied. Note
That this should be done before running the lavaan model and should
not overlap with the data or covariance matrix used to run the model.</dd>
<dt>data</dt>
<dd>supply the dataset?</dd>
<dt>n.obs</dt>
<dd>Number of observations in the test set for CV.</dd></dl>

Arguments

Calculates the fit indices — fit_indices

<dl>

<dt>model</dt>
<dd>regsem model object.</dd>


<dt>CV</dt>
<dd>cross-validation. Note that this requires splitting the dataset
into a training and test set prior to running the model. The
model should be run on the training set, with the test set
held out and then passed to CovMat=.</dd>


<dt>CovMat</dt>
<dd>If CV=T then test covariance matrix must be supplied. Note
That this should be done before running the lavaan model and should
not overlap with the data or covariance matrix used to run the model.</dd>


<dt>data</dt>
<dd>supply the dataset?</dd>


<dt>n.obs</dt>
<dd>Number of observations in the test set for CV.</dd>

</dl>

Calculates the fit indices

fit_indices: Calculates the fit indices

Description

Usage

Value

Arguments

Examples