Package: bdribs 1.0.4.1

Saurabh Mukhopadhyay

bdribs: Bayesian Detection of Potential Risk Using Inference on Blinded Safety Data

Implements Bayesian inference to detect signal from blinded clinical trial when total number of adverse events of special concerns and total risk exposures from all patients are available in the study. For more details see the article by Mukhopadhyay et. al. (2018) titled 'Bayesian Detection of Potential Risk Using Inference on Blinded Safety Data', in Pharmaceutical Statistics (to appear).

Authors:Saurabh Mukhopadhyay [aut, cre]

bdribs_1.0.4.1.tar.gz
bdribs_1.0.4.1.zip(r-4.7-any)bdribs_1.0.4.1.zip(r-4.6-any)
bdribs_1.0.4.1.tar.gz(r-4.7-any)bdribs_1.0.4.1.tar.gz(r-4.6-any)
bdribs_1.0.4.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
bdribs/json (API)

# Install 'bdribs' in R:
install.packages('bdribs', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))
Uses libs:
  • jags– Just Another Gibbs Sampler for Bayesian MCMC
  • c++– GNU Standard C++ Library v3

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

jagscpp

1.00 score 3 scripts 295 downloads 3 exports 3 dependencies

Last updated from:f811dc2268. Checks:6 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK107
source / vignettesOK181
linux-releaseOK106
windows-develOK71
windows-releaseOK69
wasm-releaseOK110

Exports:bdribsbdribs.contourbdribs.sensitivity

Dependencies:codalatticerjags