Introduction
CohortMethod is an R package for performing new-user cohort studies in an observational database in the OMOP Common Data Model.
Features
- Extracts the necessary data from a database in OMOP Common Data Model format.
- 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.
- Large scale regularized regression to fit the propensity and outcome models.
- Includes function for trimming, stratifying, matching, and weighting on propensity scores.
- Includes diagnostic functions, including propensity score distribution plots and plots showing covariate balance before and after matching and/or trimming.
- Supported outcome models are (conditional) logistic regression, (conditional) Poisson regression, and (conditional) Cox regression.
System Requirements
Requires R (version 3.6.0 or higher). Installation on Windows requires RTools. Libraries used in CohortMethod require Java.
Installation
See the instructions here for configuring your R environment, including RTools and Java.
In R, use the following commands to download and install CohortMethod:
install.packages("remotes")
remotes::install_github("ohdsi/CohortMethod")- Optionally, run this to check if CohortMethod was correctly installed:
connectionDetails <- createConnectionDetails(dbms="postgresql",
server="my_server.org",
user = "joe",
password = "super_secret")
checkCmInstallation(connectionDetails)Where dbms, server, user, and password need to be changed to the settings for your database environment. Type
?createConnectionDetailsfor more details on how to configure your database connection.
User Documentation
Documentation can be found on the package website.
PDF versions of the documentation are also available:
- Vignette: Single studies using the CohortMethod package
- Vignette: Running multiple analyses at once using the CohortMethod package
- Package manual: CohortMethod.pdf
Support
- Developer questions/comments/feedback: OHDSI Forum
- We use the GitHub issue tracker for all bugs/issues/enhancements
Contributing
Read here how you can contribute to this package.