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.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 248 downloads 3 exports 3 dependencies

Last updated from:f811dc2268. Checks:4 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK122
source / vignettesOK151
linux-release-x86_64OK104
wasm-releaseOK104

Exports:bdribsbdribs.contourbdribs.sensitivity

Dependencies:codalatticerjags