This intensive workshop provides a comprehensive exploration of causal inference techniques, focusing on the use of propensity scores and advanced methodologies to derive robust conclusions in research across diverse fields. Led by Professor Elizabeth Stuart, participants will gain practical skills in applying these methods using R, enhancing their analytical capabilities and improving the credibility of their research findings.

Topics Covered
Purpose of Causal Inference , Identifying Causal Questions , Understanding Confounding , Key Assumptions , Estimating Propensity Scores , Balance Assessment , Matching Techniques , Weighting Methods , Common Pitfalls , Propensity Scores in R , Sensitivity Analysis Techniques , Subclassification on the Propensity Score , Addressing High-Dimensional Covariates , Combining Propensity Scores with Other Methods , Using R for Advanced Techniques , Instrumental Variables Approach , Regression Discontinuity Design , Machine Learning in Causal Inference , Handling Time-Dependent Confounding , Interpreting and Communicating Results , Implementation in R