Causal Survival Analysis

This repository contains the materials for the Causal Survival Analysis in Follow-up Studies workshop presented at the Kolokotrones Symposium at Harvard TH Chan School of Public Health on November 2, 2018, and developed by Ellie Caniglia, Ellie Murray, and Lucia Petito.

This workshop is designed to provide an overview to causal inference for survival outcomes with point exposures or time-varying exposures for which static interventions, which are known at baseline, are of interest using inverse probability weighting. A static intervention is one where the exposure should take the same value at every time point (e.g. continuous treatment versus no treatment).

The data for the workshop are a simulated version of the Coronary Drug Project trial. The workshop is available for both SAS and R users. Please ensure that you have downloaded the correct version of the dataset for your preferred coding language. The workshop instructions are provided as a single file regardless of programming language. A solutions manual will be available upon completion of the live version of the workshop.

Please direct any comments, errors, or suggestions to Ellie Murray at [email protected].