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 |