A SEMtree object obtained from <code><a rd-options="" href="/link/semtree?package=semtree&version=0.9.12" data-mini-rdoc="semtree::semtree">semtree</a></code>

tree

Default = TRUE. Only the terminal nodes (leafs) are printed. If set to FALSE, all node standard errors are written to the <code>data.frame</code>.

leafs.only

Returns a table of standard errors with columns corresponding to freely estimated standard errors and rows corresponding to nodes in the tree.

se.semtree

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 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.

Andreas M. Brandmaier andy@brandmaier.de

semtree

Recursive Partitioning for Structural Equation Models

Andreas M. Brandmaier 

John J. Prindle 

se.semtree function

A SEMtree object obtained from <code><a rd-options='' href='semtree'>semtree</a></code>

se.semtree: SEMtrees Parameter Estimates Standard Error Table

Description

Usage

Arguments

Value

Details

References

See Also