Recursive Partitioning for Structural Equation Models R package semtree version 0.9.23 CRAN Task View: MachineLearning (https://CRAN.R-project.org/view=MachineLearning) CRAN Task View: MixedModels (https://CRAN.R-project.org/view=MixedModels) CRAN Task View: Psychometrics (https://CRAN.R-project.org/view=Psychometrics) 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>. Software 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 Andreas M. Brandmaier <andy@brandmaier.de> Comprehensive R Archive Network (CRAN) Andreas M. Brandmaier [aut, cre], John J. Prindle [aut], Manuel Arnold [aut], Caspar J. Van Lissa [aut], Moritz John [ctb] GPL-3 2025-11-26 application/tgz https://CRAN.R-project.org/package=semtree doi:10.32614/CRAN.package.semtree en-US