Some Bayesian Methods for Causal Inference

We discuss several different areas where Bayesian inference can make a difference in causal inference. These areas include learning from noisy experiments, generalization to new scenarios, meta-analysis, decision analysis, and models for measurement error. We discuss applications in biology, psychology, marketing, and other areas, and these lead to open questions, challenges, and places where we're stuck.