Publications [#257620] of James O. Berger
Papers Published
- Berger, JO; Wang, X; Shen, L. "A Bayesian approach to subgroup identification.." Journal of Biopharmaceutical Statistics 24.1 (January, 2014): 110-129. [24392981], [doi]
(last updated on 2024/01/01)Abstract:
This article discusses subgroup identification, the goal of which is to determine the heterogeneity of treatment effects across subpopulations. Searching for differences among subgroups is challenging because it is inherently a multiple testing problem with the complication that test statistics for subgroups are typically highly dependent, making simple multiplicity corrections such as the Bonferroni correction too conservative. In this article, a Bayesian approach to identify subgroup effects is proposed, with a scheme for assigning prior probabilities to possible subgroup effects that accounts for multiplicity and yet allows for (preexperimental) preference to specific subgroups. The analysis utilizes a new Bayesian model selection methodology and, as a by-product, produces individual probabilities of treatment effect that could be of use in personalized medicine. The analysis is illustrated on an example involving subgroup analysis of biomarker effects on treatments.