Important objectives in the development of stratified medicines include the identification and
confirmation of subgroups of patients with a beneficial treatment effect and a positive benefit …

This article discusses subgroup identification, the goal of which is to determine the
heterogeneity of treatment effects across subpopulations. Searching for differences among …

It is well known that both the direction and magnitude of the treatment effect in clinical trials
are often affected by baseline patient characteristics (generally referred to as biomarkers) …

In multi-parameter models, reference priors typically depend on the parameter or quantity of
interest, and it is well known that this is necessary to produce objective posterior …

Background It is well recognized that treatment effects may not be homogeneous across the
study population. Subgroup analyses constitute a fundamental step in the assessment of …

Background In a pharmaceutical drug development setting, possible interactions between
the treatment and particular baseline clinical or demographic factors are often of interest …

Hierarchical models play three important roles in modeling causal effects:(i) accounting for
data collection, such as in stratified and split-plot experimental designs;(ii) adjusting for …

We provide a Bayesian decision theoretic approach to finding subgroups that have elevated
treatment effects. Our approach separates the modeling of the response variable from the …

Recent studies have demonstrated regional differences in marine ecosystem C: N: P with
implications for carbon and nutrient cycles. Due to strong co-variance, temperature and …

We propose a nonparametric Bayesian local clustering (NoB-LoC) approach for
heterogeneous data. NoB-LoC implements inference for nested clusters as posterior …