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SMARTbayesR (version 2.0.0)

Bayesian Set of Best Dynamic Treatment Regimes and Sample Size in SMARTs for Binary Outcomes

Description

Permits determination of a set of optimal dynamic treatment regimes and sample size for a SMART design in the Bayesian setting with binary outcomes. Please see Artman (2020) .

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Version

Install

install.packages('SMARTbayesR')

Monthly Downloads

196

Version

2.0.0

License

GPL-3

Maintainer

William Artman

Last Published

September 30th, 2021

Functions in SMARTbayesR (2.0.0)

PosteriorTrtSeqProb

Treatment Sequence Response Probabilities from Dataset
LogRR

Log Risk Ratios for Embedded Dynamic Treatment Regimes
RD

Risk Differences for Embedded Dynamic Treatment Regimes
PosteriorEDTRProbs

Convert Treatment Sequence Draws into Embedded Dynamic Treatment Regime Draws
LogOR

Log-Odds Ratios for Embedded Dynamic Treatment Regimes
SMARTbayesR

SMARTbayesR: A package for Bayesian computation of optimal embedded dynamic treatment regimes and sample size determination with binary outcomes
PowerBayesian

Power Calculation for a SMART with a Binary Outcome
SimDesign1

Simulate a SMART with Design 1
MCBUpperLimits

Simultaneous Upper Credible Intervals