Assignments from STAT 31900 (Introduction to Causal Inference), taught by Dr. Guanglei Hong, at UChicago.
- Homework 1 explores introductory topics in causal inference---including the potential outcomes framework, the prima facie effect, and confounding---using multiple regression analysis.
- Homework 2 explores the use of various propensity score-based methods for causal inference, including matching, stratification, inverse probability of treatment weighting (IPTW), and marginal mean weighting through stratification (MMWS).
- Homework 3 explores the use of various econometric techniques for causal inference, including instrumental variables, regression discontinuity designs, and difference-in-differences analyses.