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: | 0.9.18 |
| Depends: | R (≥ 2.10), OpenMx (≥ 2.6.9) |
| Imports: | bitops, sets, digest, rpart, rpart.plot (≥ 3.0.6), plotrix, cluster, stringr, lavaan, ggplot2, tidyr, methods, strucchange, sandwich, zoo, crayon, clisymbols, future.apply, data.table |
| Suggests: | knitr, rmarkdown, viridis, MASS, psychTools, testthat |
| Published: | 2022-05-13 |
| Author: | Andreas M. Brandmaier [aut, cre], John J. Prindle [aut], Manuel Arnold [aut], Caspar J. Van Lissa [aut] |
| Maintainer: | Andreas M. Brandmaier <andy at brandmaier.de> |
| License: | GPL-3 |
| NeedsCompilation: | no |
| Materials: | NEWS |
| In views: | MachineLearning, Psychometrics |
| CRAN checks: | semtree results |
| Reference manual: | semtree.pdf |
| Vignettes: |
Constraints in semtree SEM Forests Getting Started with the semtree package Score-based Tests Focus parameters in SEM forests |
| Package source: | semtree_0.9.18.tar.gz |
| Windows binaries: | r-devel: semtree_0.9.18.zip, r-release: semtree_0.9.18.zip, r-oldrel: semtree_0.9.18.zip |
| macOS binaries: | r-release (arm64): semtree_0.9.18.tgz, r-oldrel (arm64): semtree_0.9.18.tgz, r-release (x86_64): semtree_0.9.18.tgz, r-oldrel (x86_64): semtree_0.9.18.tgz |
| Old sources: | semtree archive |
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