Case-control studies and Bayesian inference.

Abstract

We outline the methods of Bayesian inference for applications to case-control studies. These methods appear as the natural way of making inferences, since much of the controversy that surrounds a specific case-control study is subjective. We derive conjugate prior distributions of exposure, posterior distributions of the ratio of the odds of being incident with a disease both with and without exposure to a potential causal agent, and convenient approximations. In particular, we show how one may carry out 'case-control studies' without necessarily having a control group. We illustrate these ideas with the data that first showed the relationship between in utero exposure to diethylstilbestrol and cancer of the vagina in young girls.