# 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.

# beanz 2.0

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

• 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

# beanz 2.2

• Minor fix in bzSummary() and bzSummaryComp(). Instead of returning matrix, they now return data frames.

# Reference manual

install.packages("beanz")

2.4 by Chenguang Wang, a month 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

Imports rstan, rstantools, survival, loo

Depends on Rcpp, methods

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