Bayesian Causal Inference

This lecture will review the problem of causal inference from observational sample data or a mixture of observational sample and experimental data, particularly in the area of graphical causal modeling from a Bayesian perspective.

Topics covered:

• Potential Outcome Framework (Rubin)
• The Fundamental Problem of Causal Inference
• Bayesian Inference of Causal Effects
• Causal Bayesian Networks

References:

• Introduction to Causal Inference