BACCT: Bayesian Augmented Control for Clinical Trials
Version 1.0

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.

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AuthorHongtao Zhang [aut, cre], Qi Tang [aut]
Date of publication2016-06-25 19:07:22
MaintainerHongtao Zhang <hongtao.zhang@abbvie.com>
LicenseGPL (>= 3)
Version1.0
Package repositoryView on CRAN
InstallationInstall the latest version of this package by entering the following in R:
install.packages("BACCT")

Man pages

BAC_binom: Bayesian Augmented Control for Binary Responses
BACCT-package: Bayesian Augmented Control for Clinical Trials
decision_eval: Evaluating a Decision Rule
heatmap_decision: Heatmap for Decision Rules
plot.BACdecision: Generateing Plot(s) Used for Decision Rule Evaluation
summary.BAC: Summarizing BAC

Functions

BACCT Man page
BACCT-package Man page
BAC_binom Man page Source code
decision_eval Man page Source code
heatmap_decision Man page Source code
plot.BACdecision Man page Source code
summary.BAC Man page Source code

Files

NAMESPACE
R
R/plot.BACdecision.R
R/BACCT.R
R/sysdata.rda
R/decision_eval.R
R/BAC_binom.R
R/summary.BAC.R
R/heatmap_decision.R
MD5
DESCRIPTION
man
man/decision_eval.Rd
man/BACCT-package.Rd
man/summary.BAC.Rd
man/BAC_binom.Rd
man/plot.BACdecision.Rd
man/heatmap_decision.Rd
BACCT documentation built on May 19, 2017, 11:32 p.m.