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CohortMethod
View on CRAN: Click
here
Download and install CohortMethod package within the R console
Install from CRAN:
install.packages("CohortMethod")
Install from Github:
library("remotes")
install_github("cran/CohortMethod") Install by package version:
library("remotes")
install_version("CohortMethod", "6.0.3") Attach the package and use:
library("CohortMethod")
Maintained by
Martijn Schuemie
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2026-03-21
Latest Update: 2026-03-21
Description:
Functions for performing comparative cohort studies in an observational database in the Observational Medical Outcomes Partnership (OMOP) Common Data Model. Can extract all necessary data from a database. This implements large-scale propensity scores (LSPS) as described in Tian et al. (2018) <doi:10.1093/ije/dyy120>, using a large set of covariates, including for example all drugs, diagnoses, procedures, as well as age, comorbidity indexes, etc. Large scale regularized regression is used to fit the propensity and outcome models as described in Suchard et al. (2013) <doi:10.1145/2414416.2414791>. Functions are included for trimming, stratifying, (variable and fixed ratio) matching and weighting by propensity scores, as well as diagnostic functions, such as 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 (stratified) Cox regression. Also included are Kaplan-Meier plots that can adjust for the stratification or matching.
How to cite:
Martijn Schuemie (2026). CohortMethod: Comparative Cohort Method with Large Scale Propensity and Outcome Models. R package version 6.0.3, https://cran.r-project.org/web/packages/CohortMethod. Accessed 24 Oct. 2026.
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