A Bayesian approach to the interpretation of subgroup results in clinical trials.
Problems of interpretation often arise when patients who have been entered into a randomized clinical trial are post-stratified according to prognostic descriptors, and treatment comparisons performed within subgroups. In this paper a Bayesian approach to interpreting these comparisons is proposed, which takes into account the investigator's prior expectations concerning the relative magnitudes of treatment effects in different subgroups.
D001499:Bayes Theorem; D002986:Clinical Trials as Topic; D006801:Humans; D011336:Probability; D011379:Prognosis; D011897:Random Allocation; D013223:Statistics as Topic