blendR: Blended Survival Curves
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
[aut],
Zhaojing Che
[aut, cph, cre] |
Maintainer: |
Zhaojing Che <blendr-pkg at proton.me> |
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 |
Documentation:
Downloads:
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