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pseudoCure: A Pseudo-Observations Approach for Analyzing Survival Data with a Cure Fraction

A collection of easy-to-use tools for regression analysis of survival data with a cure fraction proposed in Su et al. (2022) <doi:10.1177/09622802221108579>. The modeling framework is based on the Cox proportional hazards mixture cure model and the bounded cumulative hazard (promotion time cure) model. The pseudo-observations approach is utilized to assess covariate effects and embedded in the variable selection procedure.

Version: 1.0.0
Depends: R (≥ 4.2.0)
Imports: Rcpp, MASS, ggplot2, ggpubr, rlang
LinkingTo: Rcpp, RcppArmadillo
Published: 2025-02-06
DOI: 10.32614/CRAN.package.pseudoCure
Author: Sy Han (Steven) Chiou [aut, cre], Chien-Lin Su [aut], Feng-Chang Lin [aut]
Maintainer: Sy Han (Steven) Chiou <schiou at smu.edu>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: yes
Materials: README
CRAN checks: pseudoCure results

Documentation:

Reference manual: pseudoCure.pdf

Downloads:

Package source: pseudoCure_1.0.0.tar.gz
Windows binaries: r-devel: pseudoCure_1.0.0.zip, r-release: pseudoCure_1.0.0.zip, r-oldrel: pseudoCure_1.0.0.zip
macOS binaries: r-devel (arm64): pseudoCure_1.0.0.tgz, r-release (arm64): pseudoCure_1.0.0.tgz, r-oldrel (arm64): pseudoCure_1.0.0.tgz, r-devel (x86_64): pseudoCure_1.0.0.tgz, r-release (x86_64): pseudoCure_1.0.0.tgz, r-oldrel (x86_64): pseudoCure_1.0.0.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.