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.
Version: 3.1 Depends: R (≥ 3.4.0), Rcpp (≥ 0.12.0), methods Imports: rstan (≥ 2.18.1), rstantools (≥ 1.5.0), survival, loo, RcppParallel (≥ 5.0.1) LinkingTo: StanHeaders (≥ 2.18.0), rstan (≥ 2.18.1), BH (≥ 1.66.0), Rcpp (≥ 0.12.0), RcppEigen (≥ 0.3.3.3.0), RcppParallel (≥ 5.0.1) Suggests: knitr, shiny, rmarkdown, pander, shinythemes, DT, testthat Published: 2023-08-09 DOI: 10.32614/CRAN.package.beanz Author: Chenguang Wang [aut, cre], Ravi Varadhan [aut], Trustees of Columbia University [cph] (tools/make_cpp.R, R/stanmodels.R) Maintainer: Chenguang Wang <cwang68 at jhmi.edu> License: GPL (≥ 3) NeedsCompilation: yes SystemRequirements: GNU make Citation: beanz citation info Materials: NEWS CRAN checks: beanz results Documentation: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=beanz to link to this page.
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