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:
bipd_0.3.tar.gz
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bipd.pdf |bipd.html✨
bipd/json (API)
NEWS
# Install 'bipd' in R: |
install.packages('bipd', repos = c('https://mikejseo.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/mikejseo/bipd/issues
Last updated 2 years agofrom:35fab266c7. Checks:OK: 7. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 05 2024 |
R-4.5-win | OK | Nov 05 2024 |
R-4.5-linux | OK | Nov 05 2024 |
R-4.4-win | OK | Nov 05 2024 |
R-4.4-mac | OK | Nov 05 2024 |
R-4.3-win | OK | Nov 05 2024 |
R-4.3-mac | OK | Nov 05 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
Rendered fromImputing-missing-values-in-IPD.Rmd
usingknitr::rmarkdown
on Nov 05 2024.Last update: 2022-01-22
Started: 2022-01-21
IPD meta-analysis
Rendered fromIPD-meta-analysis.Rmd
usingknitr::rmarkdown
on Nov 05 2024.Last update: 2022-05-25
Started: 2022-01-21
IPD meta-analysis-with-missing-data
Rendered fromIPD-meta-analysis-with-missing-data.Rmd
usingknitr::rmarkdown
on Nov 05 2024.Last update: 2022-05-25
Started: 2022-03-03