Movatterモバイル変換


[0]ホーム

URL:


pseudoCure: A Pseudo-Observations Approach for Analyzing Survival Data witha 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.html ,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-release (arm64):pseudoCure_1.0.0.tgz, r-oldrel (arm64):pseudoCure_1.0.0.tgz, r-release (x86_64):pseudoCure_1.0.0.tgz, r-oldrel (x86_64):pseudoCure_1.0.0.tgz

Linking:

Please use the canonical formhttps://CRAN.R-project.org/package=pseudoCureto link to this page.


[8]ページ先頭

©2009-2025 Movatter.jp