Stratified Analysis of `Probabilities of Causation'

This paper derives new bounds for the probabilities of causation defined by Pearl (2000), namely, the probability that one observed event was a necessary (or sufficient, or both) cause of another. Tian and Pearl (2000a, 2000b) showed how to bound these probabilities using information from experimental and observational studies,with minimal assumptions about the data-generating process. We derive narrower bounds using covariates measurements that might be available in the studies. In addition, we provide identifiable case under no-prevention assumption and discuss the covariate selection problem from the viewpoint of estimation accuracy. These results provides more accurate information for public policy, legal determination of responsibility and personal decision making.