beanz: Bayesian Analysis of Heterogeneous Treatment Effect

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) <DOI:10.18637/jss.v085.i07> for further details.

Package details

AuthorChenguang Wang [aut, cre], Ravi Varadhan [aut], Trustees of Columbia University [cph] (tools/make_cpp.R, R/stanmodels.R)
MaintainerChenguang Wang <>
LicenseGPL (>= 3)
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:

Try the beanz package in your browser

Any scripts or data that you put into this service are public.

beanz documentation built on May 2, 2019, 4:01 a.m.