semtree: Recursive Partitioning for Structural Equation Models (original) (raw)
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>.
| Version: | 0.9.22 |
|---|---|
| Depends: | R (≥ 2.10), OpenMx (≥ 2.6.9) |
| Imports: | rpart, rpart.plot (≥ 3.0.6), lavaan, cluster, ggplot2, tidyr, dplyr, methods, strucchange, sandwich, zoo, crayon, clisymbols, future.apply, data.table, expm, gridBase |
| Suggests: | knitr, rmarkdown, viridis, MASS, psychTools, testthat, future, ctsemOMX |
| Published: | 2025-07-28 |
| DOI: | 10.32614/CRAN.package.semtree |
| Author: | Andreas M. Brandmaier [aut, cre], John J. Prindle [aut], Manuel Arnold [aut], Caspar J. Van Lissa [aut] |
| Maintainer: | Andreas M. Brandmaier |
| BugReports: | https://github.com/brandmaier/semtree/issues |
| License: | GPL-3 |
| URL: | https://github.com/brandmaier/semtree |
| NeedsCompilation: | no |
| Language: | en-US |
| Materials: | NEWS |
| In views: | MachineLearning, MixedModels, Psychometrics |
| CRAN checks: | semtree results |
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