# -------------------------------------------- # CITATION file created with {cffr} R package # See also: https://docs.ropensci.org/cffr/ # -------------------------------------------- cff-version: 1.2.0 message: 'To cite package "blendR" in publications use:' type: software license: GPL-3.0-or-later title: 'blendR: Blended Survival Curves' version: 1.0.0 doi: 10.32614/CRAN.package.blendR identifiers: - type: url value: https://StatisticsHealthEconomics.github.io/blendR/ abstract: 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) . authors: - family-names: Green given-names: Nathan email: n.green@ucl.ac.uk orcid: https://orcid.org/0000-0003-2745-1736 website: https://ror.org/02jx3x895 - family-names: Che given-names: Zhaojing email: blendr-pkg@proton.me orcid: https://orcid.org/0000-0003-2245-1606 website: https://ror.org/052gg0110 repository: https://statisticshealtheconomics.r-universe.dev repository-code: https://github.com/StatisticsHealthEconomics/blendR/issues/ commit: 37756194473dd1e41ca4794cf4dbc8de3112fbb9 url: https://github.com/StatisticsHealthEconomics/blendR/ date-released: '2025-10-16' contact: - family-names: Che given-names: Zhaojing email: blendr-pkg@proton.me orcid: https://orcid.org/0000-0003-2245-1606 website: https://ror.org/052gg0110