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tipmap: Tipping Point Analysis for Bayesian Dynamic Borrowing

Tipping point analysis for clinical trials that employ Bayesian dynamic borrowing via robust meta-analytic predictive (MAP) priors. Further functions facilitate expert elicitation of a primary weight of the informative component of the robust MAP prior and computation of operating characteristics. Intended use is the planning, analysis and interpretation of extrapolation studies in pediatric drug development, but applicability is generally wider.

Version: 0.5.2
Depends: R (≥ 3.5.0)
Imports: dplyr, magrittr, purrr, ggplot2, RBesT, assertthat, stats, furrr, future
Suggests: knitr, rmarkdown, tidyr, tibble, testthat (≥ 3.0.0)
Published: 2023-08-14
Author: Christian Stock ORCID iD [aut, cre], Morten Dreher [aut], Emma Torrini [ctb], Boehringer Ingelheim Pharma GmbH & Co. KG [cph, fnd]
Maintainer: Christian Stock <christian.stock at boehringer-ingelheim.com>
BugReports: https://github.com/Boehringer-Ingelheim/tipmap/issues
License: Apache License 2.0
URL: https://github.com/Boehringer-Ingelheim/tipmap
NeedsCompilation: no
Materials: README NEWS
CRAN checks: tipmap results

Documentation:

Reference manual: tipmap.pdf
Vignettes: Determining a weight of the informative prior component
Introduction to the 'tipmap' package

Downloads:

Package source: tipmap_0.5.2.tar.gz
Windows binaries: r-devel: tipmap_0.5.2.zip, r-release: tipmap_0.5.2.zip, r-oldrel: tipmap_0.5.2.zip
macOS binaries: r-release (arm64): tipmap_0.5.2.tgz, r-oldrel (arm64): tipmap_0.5.2.tgz, r-release (x86_64): tipmap_0.5.2.tgz, r-oldrel (x86_64): tipmap_0.5.2.tgz
Old sources: tipmap archive

Linking:

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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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