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BACCT
View on CRAN: Click
here
Download and install BACCT package within the R console
Install from CRAN:
install.packages("BACCT")
Install from Github:
library("remotes")
install_github("cran/BACCT")
Install by package version:
library("remotes")
install_version("BACCT", "1.0")
Attach the package and use:
library("BACCT")
Maintained by
Hongtao Zhang
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2016-06-25
Latest Update: 2016-06-25
Description:
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.
How to cite:
Hongtao Zhang (2016). BACCT: Bayesian Augmented Control for Clinical Trials. R package version 1.0, https://cran.r-project.org/web/packages/BACCT
Previous versions and publish date:
No previous versions
Other packages that cited BACCT R package
View BACCT citation profile
Other R packages that BACCT depends,
imports, suggests or enhances
Functions, R codes and Examples using
the BACCT R package
Some associated functions: BACCT-package . BAC_binom . decision_eval . heatmap_decision . plot.BACdecision . summary.BAC .
Some associated R codes: BACCT.R . BAC_binom.R . decision_eval.R . heatmap_decision.R . plot.BACdecision.R . summary.BAC.R . Full BACCT package functions and examples
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