CohortMethod is part of HADES.
CohortMethod is an R package for performing new-user cohort studies in an observational database in the OMOP Common Data Model.
- 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 and matching 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.
Propensity (preference score) distribution
Covariate balance plot
CohortMethod is an R package, with some functions implemented in C++.
Requires R (version 3.6.0 or higher). Installation on Windows requires RTools. Libraries used in CohortMethod require Java.
See the instructions here for configuring your R environment, including RTools and Java.
In R, use the following commands to download and install CohortMethod:
- Optionally, run this to check if CohortMethod was correctly installed:
connectionDetails <- createConnectionDetails(dbms="postgresql",
user = "joe",
password = "super_secret")
Where dbms, server, user, and password need to be changed to the settings for your database environment. Type
for more details on how to configure your database connection.
Documentation can be found on the package website.
PDF versions of the documentation are also available:
Read here how you can contribute to this package.
CohortMethod is licensed under Apache License 2.0
CohortMethod is being developed in R Studio.
CohortMethod is actively being used in several studies and is ready for use.
- This project is supported in part through the National Science Foundation grant IIS 1251151.