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blendR: Blended Survival Curves (original) (raw)

Create a blended curve from two survival curves, which is particularly useful for survival extrapolation in health technology assessment. The main idea is to mix a flexible model that fits the observed data well with a parametric model that encodes assumptions about long-term survival. The two curves are blended into a single survival curve that is identical to the first model over the range of observed times and gradually approaches the parametric model over the extrapolation period based on a given weight function. This approach allows for the inclusion of external information, such as data from registries or expert opinion, to guide long-term extrapolations, especially when dealing with immature trial data. See Che et al. (2022) <doi:10.1177/0272989X221134545>.

Version: 1.0.0
Depends: R (≥ 4.4.0)
Imports: dplyr, flexsurv, ggplot2, manipulate, sn, survHE, tibble
Suggests: INLA, knitr, remotes, rlang, rmarkdown, survHEhmc, survival, testthat (≥ 3.0.0)
Published: 2025-09-03
DOI: 10.32614/CRAN.package.blendR
Author: Nathan Green ORCID iD ROR ID [aut], Zhaojing Che ORCID iD ROR ID [aut, cph, cre]
Maintainer: Zhaojing Che
BugReports: https://github.com/StatisticsHealthEconomics/blendR/issues/
License: GPL (≥ 3)
URL: https://github.com/StatisticsHealthEconomics/blendR/,https://StatisticsHealthEconomics.github.io/blendR/
NeedsCompilation: no
Additional_repositories: https://giabaio.r-universe.dev,https://inla.r-inla-download.org/R/stable
Materials: README, NEWS
CRAN checks: blendR results

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