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


News

beanz 2.0

  • Added a NEWS.md file to track changes to the package.

  • Added unit test

  • Made it consistent throughout the software and the manuscript that the half-normal prior is for $\omega$ rather than $\omega^{2}$

  • Added initial step-size as an option of the sampler

  • Added adapt-delta as an option in the software and set the default value to 0.95

  • Added explicit report of Rhat in the results and warnings for problematic convergence based on Rhat summaries

  • Removed in shiny the option HMC vs. Fixed-params

  • The Stan models are optimized by vectorization and non-centered parameterization

  • Updated the GUI to allow the user to enter numerical values directly for priors

  • Added looic as the measure of goodness of fit and the basis for model comparison

  • Renamed the parameters in lst.par.pri to match with the model instruction page

  • Added line for generating results for no subgroup effect model in relevant example code

  • Added model information to the output from function r.rpt.tbl

Reference manual

It appears you don't have a PDF plugin for this browser. You can click here to download the reference manual.

install.packages("beanz")

2.3 by Chenguang Wang, 12 days ago


Browse source code at https://github.com/cran/beanz


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


Documentation:   PDF Manual  


GPL (>= 3) license


Imports rstan, rstantools, survival, loo

Depends on Rcpp, methods

Suggests knitr, shiny, anoint, rmarkdown, pander, shinythemes, DT, testthat

Linking to StanHeaders, rstan, BH, Rcpp, RcppEigen

System requirements: GNU make


See at CRAN