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curesurv: Mixture and Non Mixture Parametric Cure Models to Estimate Cure Indicators

Fits a variety of cure models using excess hazard modeling methodology such as the mixture model proposed by Phillips et al. (2002) <doi:10.1002/sim.1101> The Weibull distribution is used to represent the survival function of the uncured patients; Fits also non-mixture cure model such as the time-to-null excess hazard model proposed by Boussari et al. (2020) <doi:10.1111/biom.13361>.

Version: 0.1.1
Depends: R (≥ 3.5), stringr, survival
Imports: numDeriv, stats, randtoolbox, bbmle, optimx, Formula, Deriv, statmod
Suggests: testthat, knitr, rmarkdown, xhaz, survexp.fr
Published: 2024-09-17
DOI: 10.32614/CRAN.package.curesurv
Author: Juste Goungounga ORCID iD [aut, cre], Judith Breaud ORCID iD [aut], Olayide Boussari ORCID iD [aut], Valerie Jooste ORCID iD [aut]
Maintainer: Juste Goungounga <juste.goungounga at ehesp.fr>
License: GPL (≥ 3)
NeedsCompilation: no
Citation: curesurv citation info
Materials: README NEWS
CRAN checks: curesurv results

Documentation:

Reference manual: curesurv.pdf
Vignettes: Vignette_tneh (source, R code)
How to estimate a new mixture cure model for increased risk of non cancer death (source, R code)

Downloads:

Package source: curesurv_0.1.1.tar.gz
Windows binaries: r-devel: curesurv_0.1.1.zip, r-release: curesurv_0.1.1.zip, r-oldrel: curesurv_0.1.1.zip
macOS binaries: r-release (arm64): curesurv_0.1.1.tgz, r-oldrel (arm64): curesurv_0.1.1.tgz, r-release (x86_64): curesurv_0.1.1.tgz, r-oldrel (x86_64): curesurv_0.1.1.tgz

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.