Causal Inference

Course Schedule

DateTopicsSlides
Part 1. Introduction  
2025-02-181-1. Introduction to Causal InferencePart 1-1
2025-02-251-2. Counterfactual Framework and Causal EstimandsPart 1-2
2025-03-041-3. Assumption and IdentificationPart 1-3
Part 2. Randomized Experiments  
2025-03-112-1. Treatment Assignment & Experimental DesignPart 2-1
2025-03-182-2. Completely Randomized ExperimentPart 2-2
2025-03-252-3. Covariate Imbalance in Randomized ExperimentsPart 2-3
Part 3. Observational Studies with Measured Confounding  
2025-04-013-1. Stratification and StandardizationPart 3-1 (update)
2025-04-013-1*. Causal Mediation Analysis (Intro)Part 3-1*
2025-04-153-2. Weighting and MatchingPart 3-2 (0422update)
2025-04-223-3. Propensity-Score MethodsPart 3-3
2025-05-063-4. Doubly Robust MethodsPart 3-4
Part 4. Observational Studies with Unmeasured Confounding  
2025-05-064-1. Front-door CriterionPart 4-1
(Coming soon)4-2. Difference-in-Differences (DiD) Method(Coming soon)
(Coming soon)4-3. Instrumental Variable(Coming soon)
Part 5. Sensitivity Analysis  
(Coming soon)5-1. Evaluating sensitivity to exchangeability assumption violations(Coming soon)
(Coming soon)5-2. Evaluating sensitivity to positivity assumption violations(Coming soon)
Part 6. Causal Directed Acyclic Graphs (DAGs)  
(Coming soon)6-1. DAGs for selection bias and confounding bias(Coming soon)
(Coming soon)6-2. DAGs for measurement bias(Coming soon)
(Coming soon)6-3. DAGs for interaction and effect modification(Coming soon)
Part 7. Causal Mediation Analysis  
(Coming soon)7-1. Product method and difference method(Coming soon)
(Coming soon)7-2. Mediational G-formula(Coming soon)
(Coming soon)7-3. Estimation for causal mediation analysis(Coming soon)
Part 8. Causal Inference for Longitudinal Data  
(Coming soon)8-1. G-method for time-vary treatments and confounders(Coming soon)
(Coming soon)8-2. Censoring and truncation(Coming soon)
(Coming soon)8-3. Causal survival analysis and survival average causal effect(Coming soon)

Homework