evaluateDataLikelihood

This helper function is used
in the <code>semforest</code> <code>varimp</code> and
<code>proximity</code> aggregate functions.

SEM Trees and SEM Forests -- an extension of model-based decision
trees and forests to Structural Equation Models (SEM). SEM trees hierarchically
split empirical data into homogeneous groups each sharing similar data patterns
with respect to a SEM by recursively selecting optimal predictors of these
differences. SEM forests are an extension of SEM trees. They are ensembles of
SEM trees each built on a random sample of the original data. By aggregating
over a forest, we obtain measures of variable importance that are more robust
than measures from single trees. A description of the method was published by
Brandmaier, von Oertzen, McArdle, & Lindenberger (2013) <doi:10.1037/a0030001>
and Arnold, Voelkle, & Brandmaier (2020) <doi:10.3389/fpsyg.2020.564403>.

Andreas M. Brandmaier andy@brandmaier.de

semtree

Recursive Partitioning for Structural Equation Models

Andreas M. Brandmaier 

John J. Prindle 

Manuel Arnold 

Caspar J. Van Lissa 

evaluateDataLikelihood function

<dl><dt>model</dt>
<dd>A <code>OpenMx</code> model as used in <code>semtree</code>
and <code>semforest</code>.</dd>
<dt>data</dt>
<dd>Data set to apply to a fitted model.</dd>
<dt>data_type</dt>
<dd>Type of data ("raw", "cov", "cor")</dd></dl>

Arguments

Andreas M. Brandmaier, John J. Prindle

Author

Compute the Negative Two-Loglikelihood of some data given a model (either OpenMx or lavaan) — evaluateDataLikelihood

<dl>

<dt>model</dt>
<dd>A <code>OpenMx</code> model as used in <code>semtree</code>
and <code>semforest</code>.</dd>


<dt>data</dt>
<dd>Data set to apply to a fitted model.</dd>


<dt>data_type</dt>
<dd>Type of data ("raw", "cov", "cor")</dd>

</dl>

evaluateDataLikelihood: Compute the Negative Two-Loglikelihood of some data given a model (either OpenMx or lavaan)

Description

Usage

Value

Arguments

Author

References

See Also