Principles of Causal Inference
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Syllabus
The following gives a tentative list of topics to be covered in the course (not necessarily in the
order in which they will be covered).
- Why study Causation?
Pitfalls of drawing conclusions from observational data;
Simpson's paradox and its implications
- What is a causal effect? Causation versus association,
Individual causal effects, Average causal effects, Measures of Causal effects
- Randomized experiments
Estimating causal effects through randomized experiments: Randomization, conditional randomizations, standardization, inverse probability weighting
- Estimating causal effects from observational data
Identifiability conditions: Exchangeability, positivity, consistency, target trials
- Effect modification
Why effect modification matters; Stratification, stratification as a form of adjustment; matching as a form of adjustment; effect modification and adjustment methods.
- Causal interactions
Identifying causal interactions; counterfactual response types and interactions; sufficient causes; sufficient cause interaction; sufficient component causes
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Representing causal assumptions
Causal diagrams, syntax and semantics, interventions, counterfactuals
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Causal effect identifiability Do-calculus, structure of confounding, front-door and back-door criteria
- Selection bias and measurement bias The structure of selection bias and measurement bias; selection bias and confounding, selection bias and censoring, adjusting for selection bias and measurement bias
- Advanced Techniques for Causal Effects Estimation matching, inverse propensity weighting, representation learning, doubly robust estimation
- Estimating instrumental variables Identifiability conditions for instrumental variables
- Learning causal models from data independence based and score based methods
- Generalizability of causal effects causal transportability, meta analysis
- Selected Applications
- Term Project Presentations
Students should consult the Study Guide for a more detailed breakdown of topics, course materials, and specific reading assignments.
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