Assess graduate-level ability to apply propensity score methods to estimate causal treatment effects from observational healthcare data: selecting confounders, estimating scores (parametric and machine-learning), implementing matching, stratification, IPTW/weighting, diagnosing balance and common support, estimating ATE/ATT with appropriate variance, conducting sensitivity analyses for unmeasured confounding, and interpreting clinical implications; include short calculation/interpretation tasks using realistic variable descriptions.