{"id":14066753,"url":"https://github.com/OHDSI/CohortMethod","last_synced_at":"2025-07-29T23:32:13.565Z","repository":{"id":41113934,"uuid":"20774779","full_name":"OHDSI/CohortMethod","owner":"OHDSI","description":"An R package for performing new-user cohort studies in an observational database in the OMOP Common Data 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Status](https://github.com/OHDSI/CohortMethod/workflows/R-CMD-check/badge.svg)](https://github.com/OHDSI/CohortMethod/actions?query=workflow%3AR-CMD-check)\n[![codecov.io](https://codecov.io/github/OHDSI/CohortMethod/coverage.svg?branch=main)](https://codecov.io/github/OHDSI/CohortMethod?branch=main)\n\nCohortMethod is part of [HADES](https://ohdsi.github.io/Hades).\n\nIntroduction\n============\nCohortMethod is an R package for performing new-user cohort studies in an observational database in the OMOP Common Data Model. \n\nFeatures\n========\n- Extracts the necessary data from a database in OMOP Common Data Model format.\n- Uses a large set of covariates for both the propensity and outcome model, including for example all drugs, diagnoses, procedures, as well as age, comorbidity indexes, etc.\n- Large scale regularized regression to fit the propensity and outcome models.\n- Includes function for trimming, stratifying, matching, and weighting on propensity scores.\n- Includes diagnostic functions, including propensity score distribution plots and plots showing covariate balance before and after matching and/or trimming.\n- Supported outcome models are (conditional) logistic regression, (conditional) Poisson regression, and (conditional) Cox regression.\n\nScreenshots\n===========\n\u003ctable\u003e\n\u003ctr valign=\"bottom\"\u003e\n\u003ctd width = 50%\u003e\n\n\u003cimg src=\"https://github.com/OHDSI/CohortMethod/raw/main/extras/ps.png\"/\u003e\n\n\u003c/td\u003e\n\u003ctd width = 50%\u003e\n  \n\u003cimg src=\"https://github.com/OHDSI/CohortMethod/raw/main/extras/balanceScatterplot.png\"/\u003e\n\n\u003c/td\u003e\n\u003c/tr\u003e\u003ctr\u003e\n\u003ctd\u003ePropensity (preference score) distribution\u003c/td\u003e\u003ctd\u003eCovariate balance plot\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/table\u003e\n\nTechnology\n============\nCohortMethod is an R package, with some functions implemented in C++.\n\nSystem Requirements\n============\nRequires R (version 3.6.0 or higher). Installation on Windows requires [RTools](https://cran.r-project.org/bin/windows/Rtools/). Libraries used in CohortMethod require Java.\n\nInstallation\n=============\n1. See the instructions [here](https://ohdsi.github.io/Hades/rSetup.html) for configuring your R environment, including RTools and Java.\n\n2. In R, use the following commands to download and install CohortMethod:\n\n  ```r\n  install.packages(\"remotes\")\n  remotes::install_github(\"ohdsi/CohortMethod\")\n  ```\n  \n3. Optionally, run this to check if CohortMethod was correctly installed:\n\n  ```r\n  connectionDetails \u003c- createConnectionDetails(dbms=\"postgresql\",\n                                               server=\"my_server.org\",\n                                               user = \"joe\",\n                                               password = \"super_secret\")\n\n  checkCmInstallation(connectionDetails)\n  ```\n  \n  Where dbms, server, user, and password need to be changed to the settings for your database environment. Type\n  \n  ```r\n  ?createConnectionDetails\n  ``` \n  \n  for more details on how to configure your database connection.\n\nUser Documentation\n==================\nDocumentation can be found on the [package website](https://ohdsi.github.io/CohortMethod).\n\nPDF versions of the documentation are also available:\n\n* Vignette: [Single studies using the CohortMethod package](https://raw.githubusercontent.com/OHDSI/CohortMethod/main/inst/doc/SingleStudies.pdf)\n* Vignette: [Running multiple analyses at once using the CohortMethod package](https://raw.githubusercontent.com/OHDSI/CohortMethod/main/inst/doc/MultipleAnalyses.pdf)\n* Package manual: [CohortMethod.pdf](https://raw.githubusercontent.com/OHDSI/CohortMethod/main/extras/CohortMethod.pdf)\n\nSupport\n=======\n* Developer questions/comments/feedback: \u003ca href=\"http://forums.ohdsi.org/c/developers\"\u003eOHDSI Forum\u003c/a\u003e\n* We use the \u003ca href=\"https://github.com/OHDSI/CohortMethod/issues\"\u003eGitHub issue tracker\u003c/a\u003e for all bugs/issues/enhancements\n\nContributing\n============\nRead [here](https://ohdsi.github.io/Hades/contribute.html) how you can contribute to this package.\n\nLicense\n=======\nCohortMethod is licensed under Apache License 2.0\n\nDevelopment\n===========\nCohortMethod is being developed in R Studio.\n\n### Development status\n\nCohortMethod is actively being used in several studies and is ready for use.\n\n# Acknowledgements\n- This project is supported in part through the National Science Foundation grant IIS 1251151.\n","funding_links":[],"categories":["HADES R Packages","R"],"sub_categories":["Population-Level Estimation"],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2FOHDSI%2FCohortMethod","html_url":"https://awesome.ecosyste.ms/projects/github.com%2FOHDSI%2FCohortMethod","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2FOHDSI%2FCohortMethod/lists"}