Package: bipd 0.3

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.

Authors:Michael Seo [aut, cre]

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bipd.pdf |bipd.html✨
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NEWS

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

Peer review:

Bug tracker:https://github.com/mikejseo/bipd/issues

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

On CRAN:

12 exports 3 stars 0.95 score 20 dependencies 20 scripts 411 downloads

Last updated 2 years agofrom:35fab266c7. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKSep 06 2024
R-4.5-winOKSep 06 2024
R-4.5-linuxOKSep 06 2024
R-4.4-winOKSep 06 2024
R-4.4-macOKSep 06 2024
R-4.3-winOKSep 06 2024
R-4.3-macOKSep 06 2024

Exports:add.mcmcfindMissingPatterngenerate_ipdma_examplegenerate_ipdnma_examplegenerate_sysmiss_ipdma_exampleipd.runipd.run.parallelipdma.imputeipdma.model.deft.onestageipdma.model.onestageipdnma.model.onestagetreatment.effect

Dependencies:clicodadplyrfansigenericsgluelatticelifecyclemagrittrmvtnormpillarpkgconfigR6rjagsrlangtibbletidyselectutf8vctrswithr

Imputing missing values in IPD

Michael Seo

Rendered fromImputing-missing-values-in-IPD.Rmdusingknitr::rmarkdownon Sep 06 2024.

Last update: 2022-01-22
Started: 2022-01-21

IPD meta-analysis

Michael Seo

Rendered fromIPD-meta-analysis.Rmdusingknitr::rmarkdownon Sep 06 2024.

Last update: 2022-05-25
Started: 2022-01-21

IPD meta-analysis-with-missing-data

Michael Seo

Rendered fromIPD-meta-analysis-with-missing-data.Rmdusingknitr::rmarkdownon Sep 06 2024.

Last update: 2022-05-25
Started: 2022-03-03