bipd: Bayesian Individual Patient Data Meta-Analysis using 'JAGS'

We use a Bayesian approach to run individual patient data meta-analysis and network meta-analysis using 'JAGS'. The methods incorporate shrinkage methods and calculate patient-specific treatment effects as described in Seo et al. (2021) <doi:10.1002/sim.8859>. This package also includes user-friendly functions that impute missing data in an individual patient data using mice-related packages.

Version: 0.2
Depends: R (≥ 2.10)
Imports: rjags (≥ 4-6), coda (≥ 0.13), mvtnorm, dplyr
Suggests: dclone, R2WinBUGS, mice, micemd, miceadds, mitools, knitr, rmarkdown
Published: 2022-03-02
Author: Michael Seo [aut, cre]
Maintainer: Michael Seo <swj8874 at gmail.com>
License: GPL-3
NeedsCompilation: no
Citation: bipd citation info
Materials: NEWS
In views: MetaAnalysis
CRAN checks: bipd results

Documentation:

Reference manual: bipd.pdf
Vignettes: IPD meta-analysis
Imputing missing values in IPD

Downloads:

Package source: bipd_0.2.tar.gz
Windows binaries: r-devel: bipd_0.2.zip, r-release: bipd_0.2.zip, r-oldrel: bipd_0.2.zip
macOS binaries: r-release (arm64): bipd_0.2.tgz, r-oldrel (arm64): bipd_0.2.tgz, r-release (x86_64): bipd_0.2.tgz, r-oldrel (x86_64): bipd_0.2.tgz
Old sources: bipd archive

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