BACCT: Bayesian Augmented Control for Clinical Trials

Implements the Bayesian Augmented Control (BAC, a.k.a. Bayesian historical data borrowing) method under clinical trial setting by calling 'Just Another Gibbs Sampler' ('JAGS') software. In addition, the 'BACCT' package evaluates user-specified decision rules by computing the type-I error/power, or probability of correct go/no-go decision at interim look. The evaluation can be presented numerically or graphically. Users need to have 'JAGS' 4.0.0 or newer installed due to a compatibility issue with 'rjags' package. Currently, the package implements the BAC method for binary outcome only. Support for continuous and survival endpoints will be added in future releases. We would like to thank AbbVie's Statistical Innovation group and Clinical Statistics group for their support in developing the 'BACCT' package.

Version: 1.0
Depends: R (≥ 2.10)
Imports: rjags, ggplot2, reshape2
Published: 2016-06-25
Author: Hongtao Zhang [aut, cre], Qi Tang [aut]
Maintainer: Hongtao Zhang <hongtao.zhang at abbvie.com>
License: GPL (≥ 3)
NeedsCompilation: no
CRAN checks: BACCT results

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Reference manual: BACCT.pdf
Package source: BACCT_1.0.tar.gz
Windows binaries: r-devel: BACCT_1.0.zip, r-release: BACCT_1.0.zip, r-oldrel: BACCT_1.0.zip
OS X Mavericks binaries: r-release: BACCT_1.0.tgz, r-oldrel: BACCT_1.0.tgz

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