skip to Main Content

Software to Automate Implementation of Causal Inference Methods with Time-Varying Interventions

This project aims to develop SAS macros to automate the data structuring required for implementation of Causal Inference methods with electronic health records data in studies with time-varying exposures, confounding and selection bias (e.g., marginal structural modeling with inverse probability weighting). SAS macros are validated with simulated data and their applicability is evaluated using secondary data analyses in cardiovascular, diabetes, and health services research. End-user feedback is used to validate and refine the implementation and documentation of the SAS software.  

Investigator: Neugebauer, Romain

Explore all studies and publications

Back To Top