{"id":18765505,"url":"https://github.com/brandmaier/semtree","last_synced_at":"2025-04-07T16:18:10.411Z","repository":{"id":14506318,"uuid":"76649538","full_name":"brandmaier/semtree","owner":"brandmaier","description":"Recursive Partitioning for Structural Equation Models","archived":false,"fork":false,"pushed_at":"2024-12-21T20:01:31.000Z","size":31813,"stargazers_count":16,"open_issues_count":22,"forks_count":12,"subscribers_count":3,"default_branch":"master","last_synced_at":"2025-03-31T14:12:19.847Z","etag":null,"topics":["bigdata","cran","decision-tree","forest","multivariate","r","randomforest","recursive-partitioning","sem","statistical-modeling","structural-equation-modeling","structural-equation-models"],"latest_commit_sha":null,"homepage":"https://brandmaier.github.io/semtree/","language":"R","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"gpl-3.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/brandmaier.png","metadata":{"files":{"readme":"README.Rmd","changelog":"NEWS.md","contributing":null,"funding":null,"license":"LICENSE.md","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2016-12-16T11:43:51.000Z","updated_at":"2025-03-29T21:25:08.000Z","dependencies_parsed_at":"2023-12-06T13:43:42.847Z","dependency_job_id":"d5b357ce-6b41-46b6-867f-f91cf7381df7","html_url":"https://github.com/brandmaier/semtree","commit_stats":{"total_commits":339,"total_committers":9,"mean_commits":"37.666666666666664","dds":0.5014749262536873,"last_synced_commit":"7cc97e2bbc1a05602d553d2df132365f3ad2c4dd"},"previous_names":[],"tags_count":7,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/brandmaier%2Fsemtree","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/brandmaier%2Fsemtree/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/brandmaier%2Fsemtree/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/brandmaier%2Fsemtree/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/brandmaier","download_url":"https://codeload.github.com/brandmaier/semtree/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":247685628,"owners_count":20979085,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["bigdata","cran","decision-tree","forest","multivariate","r","randomforest","recursive-partitioning","sem","statistical-modeling","structural-equation-modeling","structural-equation-models"],"created_at":"2024-11-07T18:34:21.996Z","updated_at":"2025-04-07T16:18:10.393Z","avatar_url":"https://github.com/brandmaier.png","language":"R","funding_links":[],"categories":[],"sub_categories":[],"readme":"---\ntitle: \"Read Me\"\noutput: md_document\n---\n\nsemtree\n======\n\n```{r echo=FALSE}\nknitr::opts_chunk$set(\n  comment = \"#\u003e\",\n  collapse = TRUE\n)\n```\n\u003c!-- badges: start --\u003e\n[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.1116294.svg)](https://doi.org/10.5281/zenodo.1116294)\n[![cran version](http://www.r-pkg.org/badges/version/semtree)](https://cran.r-project.org/package=semtree)\n[![rstudio mirror downloads](http://cranlogs.r-pkg.org/badges/semtree)](https://github.com/r-hub/cranlogs.app)\n[![R-CMD-check](https://github.com/brandmaier/semtree/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/brandmaier/semtree/actions/workflows/R-CMD-check.yaml)\n![Code size](https://img.shields.io/github/languages/code-size/brandmaier/semtree.svg)\n![Downloads](https://cranlogs.r-pkg.org/badges/grand-total/semtree)\n\u003c!-- badges: end --\u003e\n![contributions](https://img.shields.io/badge/contributions-welcome-brightgreen.svg?style=flat)\n[![License: GPL v3](https://img.shields.io/badge/License-GPLv3-blue.svg)](https://www.gnu.org/licenses/gpl-3.0)\n\n\n## What is this?\n\nAn R package for estimating Structural Equation Model (SEM) Trees and Forests. They are a fusion of SEM and decision trees, or SEM and random forests respectively. While SEM is a confirmatory modeling technique, SEM trees and forests allow to explore whether there are predictors that provide further information about an initial, theory-based model. Potential use cases are the search for potential predictors that explain individual differences, finding omitted variables in a model, or exploring measurement invariance over a large set of predictors. A recent overview is in our latest book chapter in the SEM handbook (Brandmaier \u0026 Jacobucci, 2023). \n\n## Install\n\nInstall the latest stable version from CRAN:\n```{r eval=FALSE}\ninstall.packages(\"semtree\")\n```\n\nTo install the latest semtree package directly from GitHub, copy the following line into R:\n```{r, eval=FALSE}\nlibrary(devtools)\ndevtools::install_github(\"brandmaier/semtree\")\n\n# even better: install with package vignette (extra documentation)\ndevtools::install_github(\"brandmaier/semtree\",force=TRUE, build_opts = c())\n```\n\n## Usage\n\nPackage documentation and use-cases with runnable R code can be found on our github pages: [https://brandmaier.github.io/semtree/](https://brandmaier.github.io/semtree/).\n\nPackage vignettes (shipped with the package) contain documentation on how to use the package. Simply type this in R once you have loaded the package:\n\n```{r eval=FALSE}\nbrowseVignettes(\"semtree\")\n```\n\n## References\n\nTheory and method:\n\n- Brandmaier, A. M., \u0026 Jacobucci, R. C. (2023). Machine-learning approaches to structural equation modeling. In R. H. Hoyle (Ed.), Handbook of structural equation modeling (2nd rev. ed., pp. 722–739). Guilford Press.\n\n- Arnold, M., Voelkle, M.C., and Brandmaier, A.M. (2021). Score-guided structural equation model trees. _Frontiers in psychology_, 11, 564403.\n\n- Brandmaier, A. M., Driver, C., \u0026 Voelkle, M. C. (2019). Recursive partitioning in continuous time analysis. In K. van Montfort, J. Oud, \u0026 M. C. Voelkle (Eds.), Continuous time modeling in the behavioral and related sciences. New York: Springer.\n\n- Brandmaier, A. M., Prindle, J. J., McArdle, J. J., \u0026 Lindenberger, U. (2016). Theory-guided exploration with structural equation model forests. _Psychological Methods_, 21, 566-582. \\doi{doi:10.1037/met0000090}\n\n- Brandmaier, A. M., von Oertzen, T., McArdle, J. J., \u0026 Lindenberger, U. (2014). Exploratory data mining with structural equation model trees. In J. J. McArdle \u0026 G. Ritschard (Eds.), Contemporary issues in exploratory data mining in the behavioral sciences (pp. 96-127). New York: Routledge.\n\n- Brandmaier, A. M., von Oertzen, T., McArdle, J. J., \u0026 Lindenberger, U. (2013). Structural equation model trees. _Psychological Methods_, 18, 71-86. \\doi{doi:10.1037/a0030001}\n\nApplied examples (there are many more):\n\nBrandmaier, A. M., Ram, N., Wagner, G. G., \u0026 Gerstorf, D. (2017). Terminal decline in well-being: The role of multi-indicator constellations of physical health and psychosocial correlates. Developmental Psychology.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fbrandmaier%2Fsemtree","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fbrandmaier%2Fsemtree","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fbrandmaier%2Fsemtree/lists"}