{"id":17535568,"url":"https://github.com/tbates/umx","last_synced_at":"2025-10-24T04:01:49.394Z","repository":{"id":4288221,"uuid":"5418108","full_name":"tbates/umx","owner":"tbates","description":"Making Structural Equation Modeling (SEM) in R quick \u0026 powerful","archived":false,"fork":false,"pushed_at":"2025-03-15T02:38:51.000Z","size":40692,"stargazers_count":44,"open_issues_count":22,"forks_count":17,"subscribers_count":7,"default_branch":"master","last_synced_at":"2025-03-29T09:09:52.335Z","etag":null,"topics":["behavior-genetics","cran","genetics","openmx","psychology","r","sem","statistics","structural-equation-modeling","tutorials","twin-models","umx"],"latest_commit_sha":null,"homepage":"https://tbates.github.io/","language":"R","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/tbates.png","metadata":{"files":{"readme":"README.md","changelog":"NEWS.md","contributing":null,"funding":null,"license":null,"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":"2012-08-14T20:18:01.000Z","updated_at":"2025-03-15T02:38:55.000Z","dependencies_parsed_at":"2023-09-23T11:27:31.808Z","dependency_job_id":"71c9fd45-5d15-40d8-aef3-6d56d7a5d516","html_url":"https://github.com/tbates/umx","commit_stats":{"total_commits":3014,"total_committers":8,"mean_commits":376.75,"dds":"0.012607830126078357","last_synced_commit":"a1489ab5232133523a5aa7dd77a3b8a1b1e3221f"},"previous_names":[],"tags_count":36,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/tbates%2Fumx","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/tbates%2Fumx/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/tbates%2Fumx/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/tbates%2Fumx/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/tbates","download_url":"https://codeload.github.com/tbates/umx/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":247318745,"owners_count":20919484,"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":["behavior-genetics","cran","genetics","openmx","psychology","r","sem","statistics","structural-equation-modeling","tutorials","twin-models","umx"],"created_at":"2024-10-20T19:07:13.191Z","updated_at":"2025-10-24T04:01:49.104Z","avatar_url":"https://github.com/tbates.png","language":"R","funding_links":[],"categories":[],"sub_categories":[],"readme":"# umx\n\n\u003c!-- [![Build Status](https://www.travis-ci.com/tbates/umx.svg?branch=master)](https://www.travis-ci.com/tbates/umx) --\u003e\n[![Codecov test coverage](https://codecov.io/gh/tbates/umx/branch/master/graph/badge.svg)](https://app.codecov.io/gh/tbates/umx?branch=master)\n![Github commits](https://img.shields.io/github/commits-since/tbates/umx/latest.svg?colorB=green)\n[![cran version](http://www.r-pkg.org/badges/version/umx)](https://cran.r-project.org/package=umx)\n[![Monthly Downloads](https://cranlogs.r-pkg.org/badges/umx)](https://cranlogs.r-pkg.org/badges/umx)\n[![Total Downloads](https://cranlogs.r-pkg.org/badges/grand-total/umx)](https://cranlogs.r-pkg.org/badges/grand-total/umx)\n[![Rdoc](https://www.rdocumentation.org/badges/version/umx)](https://www.rdocumentation.org/packages/umx)\n[![DOI](https://img.shields.io/badge/doi-10.1017/thg.2019.2-yellow.svg?style=flat)](https://doi.org/10.1017/thg.2019.2)\n[![License](https://img.shields.io/cran/l/umx.svg)](https://cran.r-project.org/package=umx)\n\n[Road map](https://github.com/tbates/umx/labels/enhancement), and [Tutorials](https://tbates.github.io) (let me know what you'd like, or perhaps a book?)\n\n`umx` is a package designed to make [structural equation modeling](https://en.wikipedia.org/wiki/Structural_equation_modeling) easier, from building, to modifying and reporting.\n\n`citation(\"umx\")`\n\nYou should cite: Timothy C. Bates, Michael C. Neale, Hermine H. Maes, (2019). umx: A library for Structural Equation and Twin Modelling in R. *Twin Research and Human Genetics*, **22**, 27-41. [DOI:10.1017/thg.2019.2](https://doi.org/10.1017/thg.2019.2)\n\n\n`umx` includes high-level functions for complex models such as multi-group twin models, as well as graphical model output.\n\nInstall it from CRAN:\n\n```splus\ninstall.packages(\"umx\")\nlibrary(umx)\n?umx\n```\n\nMost functions have extensive and practical examples (even figures for the twin models): so USE THE HELP :-).\n\nSee what is on offer with '?umx'. There are online tutorials at  [tbates.github.io](http://tbates.github.io).\n\n`umx` stands for \"user\" OpenMx functions. It provides over 100 functions, but most importantly:\n\n1. `umxRAM` that makes path-based SEM in R straightforward, with `umxSummary` and `plot` for table and graphical display of your models. It can also interpret basic lavaan if you get a script in that language.\n2. A suite of twin modelling functions, such as `umxACE`.\n\nThese are supported by many low-level functions automating activities such as parameter labels, start values etc., as well as helping with data-wrangling, journal-ready presentation (try `umxAPA()` among other tasks.\n\nSome highlights include:\n\n1. Building Path Models\n\t* `umxRAM()` *# Take umxPaths + data  `data =` run and return a model, along with a `plot` and `umxSummary`*\n\t* `umxPath()` *# write paths with human-readable language like `var = ` , `mean = ` `cov = `, `fixedAt=`. Quickly define a variance and mean ('v.m. = ') and more.*\n2. Reporting output\n\t* `umxSummary(model)` # *Nice summary table, in markdown or browser. Designed for journal reporting (Χ², p, CFI, TLI, \u0026 RMSEA). Optionally show path loadings*\n\t* `plot(model, std=TRUE, digits = 3, ...)` # *Graphical model in your browser! or edit in programs like OmniGraffle*\n\t* `parameters(m1, \"below\", .1, pattern=\"_to_\"))` *# A powerful assistant to get labels and values from a model (e.g. all 'to' params, below .1 in value)*\n\t* `residuals(m1, supp=.1)` *# Show residual covariances filtered for magnitude*\n3. Modify models\n\t* `umxModify(model, update = )` *# Modify and re-run a model. You can add objects, drop or add paths, including by wildcard label matching), re-name the model, and even return the comparison. All in 1 line *\n4. Twin modeling!\n\t* `umxACE` *# Twin ACE modeling with aplomb* paths are labeled! Works with `plot()` and `umxSummary`!\n\t* `umxCP`, `umxIP`, `umxGxE`, `umxCP`, `umxGxEbiv`, `umxSexLim`\n\t* ![umxACE](https://github.com/tbates/umx/blob/master/man/figures/ACEunivariate.png)\n5. Easy-to-remember options\n\t* `umx_set_cores()`\n\t* `umx_set_optimizer()`\n6. Many more miscellaneous helpers e.g.\n\t* `umx_time(model1, model2)` reports and compares run times in a compact programmable format (also \"start\" and \"stop\" a timer)\n\t* `umxHetcor(data, use = \"pairwise.complete.obs\")` *# Compute appropriate pair-wise correlations for mixed data types.*\n\t* Dozens more: Check out the \"family links\" in `?umx` and in any help file!\n\nCode and requests welcome via Github. Tell your friends! Publish good science :-)\n\nFor thrill-seekers and collaborators only: the bleeding-edge development version is here:\n\n```splus\ninstall.packages(\"devtools\")\nlibrary(\"devtools\")\ninstall_github(\"tbates/umx\")\nlibrary(\"umx\")\n?umx\n```\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ftbates%2Fumx","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Ftbates%2Fumx","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ftbates%2Fumx/lists"}