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SMARTbayesR  

Bayesian Set of Best Dynamic Treatment Regimes and Sample Size in SMARTs for Binary Outcomes
View on CRAN: Click here


Download and install SMARTbayesR package within the R console
Install from CRAN:
install.packages("SMARTbayesR")

Install from Github:
library("remotes")
install_github("cran/SMARTbayesR")

Install by package version:
library("remotes")
install_version("SMARTbayesR", "2.0.0")



Attach the package and use:
library("SMARTbayesR")
Maintained by
William Artman
[Scholar Profile | Author Map]
First Published: 2020-11-04
Latest Update: 2021-09-30
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) <doi:10.48550/arXiv.2008.02341>.
How to cite:
William Artman (2020). SMARTbayesR: Bayesian Set of Best Dynamic Treatment Regimes and Sample Size in SMARTs for Binary Outcomes. R package version 2.0.0, https://cran.r-project.org/web/packages/SMARTbayesR. Accessed 29 Mar. 2025.
Previous versions and publish date:
1.0.0 (2020-11-04 12:40), 1.0.1 (2020-11-09 14:10), 1.0.2 (2021-04-03 21:40)
Other packages that cited SMARTbayesR R package
View SMARTbayesR citation profile
Other R packages that SMARTbayesR depends, imports, suggests or enhances
Complete documentation for SMARTbayesR
Functions, R codes and Examples using the SMARTbayesR R package
Some associated functions: LogOR . LogRR . MCBUpperLimits . PosteriorEDTRProbs . PosteriorTrtSeqProb . PowerBayesian . RD . SMARTbayesR . SimDesign1 . 
Some associated R codes: LogOR.R . LogRR.R . MCBUpperLimits.R . PosteriorEDTRProbs.R . PosteriorTrtSeqProb.R . PowerBayesian.R . RD.R . SMARTbayesR.R . SimDesign1.R . internal.R .  Full SMARTbayesR package functions and examples
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