{"id":13665903,"url":"https://github.com/leeper/reggie","last_synced_at":"2025-09-09T23:36:47.007Z","repository":{"id":70770023,"uuid":"118595705","full_name":"leeper/reggie","owner":"leeper","description":"Stata-like Regression Functionality for 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Stata-like Regression Functionality\n\nThis is a work-in-progress to explore how to design Stata-like regression modelling tools for R, namely those that allow plug-and-play variance-covariance estimation procedures and also to provide arguments to modelling functions in `data`-`formula` order (rather than the traditional `formula`-`data` order) thus enabling easy use in data analysis pipelines via `%\u003e%`.\n\nContributions and feedback are welcome on [GitHub](https://github.com/leeper/reggie/issues).\n\n## Code Examples\n\n```{r opts, echo=FALSE}\noptions(width = 120)\nknitr::opts_chunk$set(comment = \"\", warning = FALSE, message = FALSE, echo = TRUE, tidy = TRUE, size=\"small\", fig.width = 10, fig.height = 10)\n```\n\nIn addition to plug-and-play variance-covariance procedures, the `reg()` function also provides pretty print methods.\n\n```{r load}\nlibrary(\"reggie\")\n\n# reg\nreg(ChickWeight, weight ~ Time + Diet)\n\n# reg\nreg(ChickWeight, weight ~ Time + Diet, vcov_type = \"const\")\n\n# reg, vce(robust)\nreg(ChickWeight, weight ~ Time + Diet, vcov_type = \"HC0\")\n\n# reg, vce(boot)\nreg(ChickWeight, weight ~ Time + Diet, vcov_type = \"boot\")\n\n# reg, vce(cluster Chick)\nreg(ChickWeight, weight ~ Time + Diet, vcov_cluster = ~ Chick)\n\n# bootstrap, cluster(Chick) reps(5000): reg\n\n#reg(ChickWeight, weight ~ Time + Diet, vcov_cluster = ~ Chick, vcov_type = \"boot\")\n\n# DOESN'T CURRENTLY WORK, BUT WHY?\n\n# svy: reg\nlibrary(\"survey\")\ndata(api)\ndstrat \u003c- svydesign(id=~1,strata=~stype, weights=~pw, data=apistrat, fpc=~fpc)\nreg(dstrat, api00 ~ ell + meals + mobility)\n```\n\nThe \"model\" object class contains the underlying model object as its `model` argument, and methods for various commonly used generic functions (`coef()`, `vcov()`, `plot()`, `terms()`, `predict()`) are provided that behave like those operations on a standard modelling object.\n\n## Installation\n\n[![CRAN](https://www.r-pkg.org/badges/version/reggie)](https://cran.r-project.org/package=reggie)\n![Downloads](https://cranlogs.r-pkg.org/badges/reggie)\n[![Travis Build Status](https://travis-ci.org/leeper/reggie.png?branch=master)](https://travis-ci.org/leeper/reggie)\n[![Appveyor Build Status](https://ci.appveyor.com/api/projects/status/PROJECTNUMBER?svg=true)](https://ci.appveyor.com/project/leeper/reggie)\n[![codecov.io](https://codecov.io/github/leeper/reggie/coverage.svg?branch=master)](https://codecov.io/github/leeper/reggie?branch=master)\n\nThis package is not yet on CRAN. To install the latest development version you can pull a potentially unstable version directly from GitHub:\n\n```R\nif (!require(\"remotes\")) {\n    install.packages(\"remotes\")\n}\nremotes::install_github(\"leeper/reggie\")\n```\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fleeper%2Freggie","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fleeper%2Freggie","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fleeper%2Freggie/lists"}