In this program
- Treatment effects: ATE, ATT, and CATE
- Randomized experiments as gold standard
- SUTVA and consistency assumptions
- Bias decomposition: confounding
- Selection
- DAGs for causal identification (introduction)
Potential outcomes framework
DAGs for causal identification (introduction)
Causal inference · Theoretical / proof-based
Topic
DAGs for causal identification (introduction)
Graduate Causal inference — outline derived from course README sections and typical US statistics syllabi (OpenIntro / standard OER where applicable).