{"id":26448891,"url":"https://github.com/lebebr01/simglm","last_synced_at":"2025-03-18T14:42:40.911Z","repository":{"id":6585614,"uuid":"7828025","full_name":"lebebr01/simglm","owner":"lebebr01","description":"Simulate regression models","archived":false,"fork":false,"pushed_at":"2024-05-08T16:37:21.000Z","size":3327,"stargazers_count":43,"open_issues_count":5,"forks_count":12,"subscribers_count":9,"default_branch":"main","last_synced_at":"2025-02-25T06:41:15.537Z","etag":null,"topics":["power","r","simulation"],"latest_commit_sha":null,"homepage":"https://simglm.brandonlebeau.org/","language":"R","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"other","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/lebebr01.png","metadata":{"files":{"readme":"README.Rmd","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","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":"2013-01-25T20:35:03.000Z","updated_at":"2024-05-08T16:16:17.000Z","dependencies_parsed_at":"2023-02-11T21:30:34.874Z","dependency_job_id":"48fd7640-a6e9-4561-93fb-5bee54f41654","html_url":"https://github.com/lebebr01/simglm","commit_stats":{"total_commits":865,"total_committers":4,"mean_commits":216.25,"dds":0.01387283236994219,"last_synced_commit":"b34a245a27d0154db514f613bbf9042ade619505"},"previous_names":[],"tags_count":3,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/lebebr01%2Fsimglm","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/lebebr01%2Fsimglm/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/lebebr01%2Fsimglm/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/lebebr01%2Fsimglm/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/lebebr01","download_url":"https://codeload.github.com/lebebr01/simglm/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":244243772,"owners_count":20422130,"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":["power","r","simulation"],"created_at":"2025-03-18T14:42:40.231Z","updated_at":"2025-03-18T14:42:40.901Z","avatar_url":"https://github.com/lebebr01.png","language":"R","funding_links":[],"categories":[],"sub_categories":[],"readme":"# `simglm`: Tidy simulation and power analyses\n\n[![R build status](https://github.com/lebebr01/simglm/workflows/R-CMD-check/badge.svg)](https://github.com/lebebr01/simglm/actions?workflow=R-CMD-check)\n[![AppVeyor build status](https://ci.appveyor.com/api/projects/status/github/lebebr01/simglm?branch=main\u0026svg=true)](https://ci.appveyor.com/project/lebebr01/simglm)\n[![codecov.io](https://codecov.io/github/lebebr01/simglm/coverage.svg?branch=main)](https://codecov.io/github/lebebr01/simglm?branch=main)\n[![CRAN_Status_Badge](https://www.r-pkg.org/badges/version/simglm)](https://cran.r-project.org/package=simglm)\n\n\n## Package Installation\nThis package can be directly installed through CRAN:\n\n```{r cran_install, eval = FALSE}\ninstall.packages(\"simglm\")\n```\n\nThe development version of the package can be installed by using the devtools package.\n\n```{r install, eval=FALSE}\nlibrary(devtools)\ninstall_github(\"lebebr01/simglm\")\n```\n\n## Introduction to the simglm package\nThe best way to become oriented with the `simglm` package is through the package vignette. There are two ways to get to the vignettes (both will open a browser to view the vignette). Below is an example loading the \"Intro\" vignette directly:\n\n```{r vignette, eval=FALSE}\nbrowseVignettes()\nvignette(\"Intro\", package = \"simglm\")\n```\n\nNote: If you install the development version of the package, you may need to tell R to build the vignettes when installing the `simglm` package by doing the following:\n```{r install2, eval = FALSE}\ninstall_github(\"lebebr01/simglm\", build_vignettes = TRUE)\n```\n\n## Features\n\nA flexible suite of functions to simulate nested data.  \nCurrently supports the following features:\n\n* Longitudinal data simulation\n* Three levels of nesting\n* Specification of distribution of random components (random effects and random error)\n* Specification of serial correlation\n* Specification of the number of variables\n    + Ability to add time-varying covariates\n    + Specify the mean and variance of fixed covariate variables\n    + Specify floor or ceiling aspects of continuous attributes\n    + Factor variable simulation \n    + Ordinal variable simulation\n* Generation of mixture normal distributions\n* Cross sectional data simulation\n* Single level simulation\n* Power by simulation\n    + Vary parameters for a factorial simulation design.\n    + Can vary model fitted to the data to misspecify directly.\n* Simulation of missing data\n* Include other distributions for covariate simulation.\n* Continuous, Logistic (dichotomous), Poisson (count), ordinal (rating scale) outcome variables.\n* Cross classified simulation and power\n\n## Bugs/Feature Requests\n\nBugs and feature requests are welcomed. Please track these on GitHub here: \u003chttps://github.com/lebebr01/simglm/issues\u003e. I'm also open to pull requests.\n\nEnjoy!\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Flebebr01%2Fsimglm","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Flebebr01%2Fsimglm","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Flebebr01%2Fsimglm/lists"}