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beanz (version 3.1)

Bayesian Analysis of Heterogeneous Treatment Effect

Description

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.

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Version

Install

install.packages('beanz')

Monthly Downloads

307

Version

3.1

License

GPL (>= 3)

Maintainer

Last Published

August 9th, 2023

Functions in beanz (3.1)

bzGetSubgrpRaw

Get subgroup treatment effect estimation and variance
bzGailSimon

Gail-Simon Test
bzCallStan

Call STAN models
beanz-package

Bayesian Approaches for HTE Analysis
bzShiny

Run Web-Based BEANZ application
bzPredSubgrp

Predictive Distribution
bzGetSubgrp

Get subgroup treatment effect estimation and variance
bzSummary

Posterior subgroup treatment effects
bzComp

Comparison of posterior treatment effects
solvd.sub

Subject level data from SOLVD trial
bzRptTbl

Summary table of treatment effects