OHDSI/CohortMethod: New-User Cohort Method with Large Scale Propensity and Outcome Models

Functions for performing new-user cohort studies in an observational database in the OMOP Common Data Model. Can extract the necessary data from a database and use 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 is used to fit the propensity and outcome models. 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.

install.packages("remotes")
remotes::install_github("OHDSI/CohortMethod")