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: | 0.9.23 |
| 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,psych,psychTools,testthat,future,ctsemOMX |
| Published: | 2025-11-26 |
| DOI: | 10.32614/CRAN.package.semtree |
| Author: | Andreas M. Brandmaier [aut, cre], John J. Prindle [aut], Manuel Arnold [aut], Caspar J. Van Lissa [aut], Moritz John [ctb] |
| Maintainer: | Andreas M. Brandmaier <andy at brandmaier.de> |
| 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 |
| Package source: | semtree_0.9.23.tar.gz |
| Windows binaries: | r-devel:semtree_0.9.23.zip, r-release:semtree_0.9.23.zip, r-oldrel:semtree_0.9.22.zip |
| macOS binaries: | r-release (arm64):semtree_0.9.23.tgz, r-oldrel (arm64):semtree_0.9.23.tgz, r-release (x86_64):semtree_0.9.23.tgz, r-oldrel (x86_64):semtree_0.9.23.tgz |
| Old sources: | semtree archive |
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