Package: bipd 0.3
Michael Seo
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
bipd_0.3.tar.gz(r-4.5-noble)bipd_0.3.tar.gz(r-4.4-noble)
bipd_0.3.tgz(r-4.4-emscripten)bipd_0.3.tgz(r-4.3-emscripten)
bipd.pdf |bipd.html✨
bipd/json (API)
NEWS
| # Install 'bipd' in R: |
| install.packages('bipd', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 3 years agofrom:2cf2e43566. Checks:OK: 2. Indexed: no.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Dec 10 2024 |
| R-4.5-linux | OK | Dec 10 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.Rmdusingknitr::rmarkdownon Dec 10 2024.Last update: 2022-01-26
Started: 2022-01-26
IPD meta-analysis
Rendered fromIPD-meta-analysis.Rmdusingknitr::rmarkdownon Dec 10 2024.Last update: 2022-06-05
Started: 2022-01-26
IPD meta-analysis-with-missing-data
Rendered fromIPD-meta-analysis-with-missing-data.Rmdusingknitr::rmarkdownon Dec 10 2024.Last update: 2022-06-05
Started: 2022-06-05
