It is vital to assess the heterogeneity of treatment effects
(HTE) when making health care decisions for an individual patient or a group
of patients. Nevertheless, it remains challenging to evaluate HTE based
on information collected from clinical studies that are often designed and
conducted to evaluate the efficacy of a treatment for the overall population.
The Bayesian framework offers a principled and flexible approach to estimate
and compare treatment effects across subgroups of patients defined by their
characteristics. This package allows users to explore a wide range of Bayesian
HTE analysis models, and produce posterior inferences about HTE. See Wang et al.
(2018)