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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) for further details.

Maintainer: Chenguang Wang
Author(s): Chenguang Wang [aut, cre], Ravi Varadhan [aut], Trustees of Columbia University [cph] (tools/make_cpp.R, R/stanmodels.R)

License: GPL (>= 3)

Uses: loo, Rcpp, rstan, rstantools, survival, testthat, knitr, pander, shiny, rmarkdown, shinythemes, DT

Released over 1 year ago.

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