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

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>.

Version: 2.0.0
Imports: stats, utils, LaplacesDemon
Suggests: knitr, rmarkdown
Published: 2021-09-30
Author: William Artman [aut, cre]
Maintainer: William Artman <William_Artman at URMC.Rochester.edu>
License: GPL-3
NeedsCompilation: no
CRAN checks: SMARTbayesR results

Documentation:

Reference manual: SMARTbayesR.pdf
Vignettes: SMARTBayesR

Downloads:

Package source: SMARTbayesR_2.0.0.tar.gz
Windows binaries: r-devel: SMARTbayesR_2.0.0.zip, r-release: SMARTbayesR_2.0.0.zip, r-oldrel: SMARTbayesR_2.0.0.zip
macOS binaries: r-release (arm64): SMARTbayesR_2.0.0.tgz, r-oldrel (arm64): SMARTbayesR_2.0.0.tgz, r-release (x86_64): SMARTbayesR_2.0.0.tgz, r-oldrel (x86_64): SMARTbayesR_2.0.0.tgz
Old sources: SMARTbayesR archive

Linking:

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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.