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BayesFBHborrow: Bayesian Dynamic Borrowing with Flexible Baseline Hazard Function

Allows Bayesian borrowing from a historical dataset for time-to- event data. A flexible baseline hazard function is achieved via a piecewise exponential likelihood with time varying split points and smoothing prior on the historic baseline hazards. The method is described in Scott and Lewin (2024) <doi:10.48550/arXiv.2401.06082>, and the software paper is in Axillus et al. (2024) <doi:10.48550/arXiv.2408.04327>.

Version: 2.0.2
Depends: R (≥ 4.1)
Imports: dplyr, stats, survival, invgamma, mvtnorm, checkmate, magrittr, ggplot2
Suggests: tibble, readxl, testthat (≥ 3.0.0), rmarkdown, ggfortify, condSURV
Published: 2024-09-16
DOI: 10.32614/CRAN.package.BayesFBHborrow
Author: Darren Scott [aut, cre], Sophia Axillus [aut]
Maintainer: Darren Scott <darren.scott at astrazeneca.com>
License: Apache License (≥ 2)
NeedsCompilation: no
CRAN checks: BayesFBHborrow results

Documentation:

Reference manual: BayesFBHborrow.pdf

Downloads:

Package source: BayesFBHborrow_2.0.2.tar.gz
Windows binaries: r-devel: BayesFBHborrow_2.0.2.zip, r-release: BayesFBHborrow_2.0.2.zip, r-oldrel: BayesFBHborrow_2.0.2.zip
macOS binaries: r-release (arm64): BayesFBHborrow_2.0.2.tgz, r-oldrel (arm64): BayesFBHborrow_2.0.2.tgz, r-release (x86_64): BayesFBHborrow_2.0.2.tgz, r-oldrel (x86_64): BayesFBHborrow_2.0.2.tgz
Old sources: BayesFBHborrow 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.