Package: bdribs 1.0.4

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.tar.gz
bdribs_1.0.4.tar.gz(r-4.5-noble)bdribs_1.0.4.tar.gz(r-4.4-noble)
bdribs_1.0.4.tgz(r-4.4-emscripten)bdribs_1.0.4.tgz(r-4.3-emscripten)
bdribs.pdf |bdribs.html
bdribs/json (API)

# Install 'bdribs' in R:
install.packages('bdribs', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Uses libs:
  • jags– Just Another Gibbs Sampler for Bayesian MCMC
  • c++– GNU Standard C++ Library v3

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 197 downloads 3 exports 3 dependencies

Last updated 6 years agofrom:90f6feb8e1. Checks:OK: 2. Indexed: yes.

TargetResultDate
Doc / VignettesOKDec 14 2024
R-4.5-linuxOKDec 14 2024

Exports:bdribsbdribs.contourbdribs.sensitivity

Dependencies:codalatticerjags