| Literature DB >> 21225894 |
S Sivaganesan1, Purushottam W Laud, Peter Müller.
Abstract
We introduce a new approach to inference for subgroups in clinical trials. We use Bayesian model selection, and a threshold on posterior model probabilities to identify subgroup effects for reporting. For each covariate of interest, we define a separate class of models, and use the posterior probability associated with each model and the threshold to determine the existence of a subgroup effect. As usual in Bayesian clinical trial design we compute frequentist operating characteristics, and achieve the desired error probabilities by choosing an appropriate threshold(s) for the posterior probabilities. 2010 John Wiley & Sons, Ltd.Entities:
Mesh:
Year: 2010 PMID: 21225894 DOI: 10.1002/sim.4108
Source DB: PubMed Journal: Stat Med ISSN: 0277-6715 Impact factor: 2.373