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 |
| Reference manual: | pseudoCure.pdf |
| 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): not available, r-release (x86_64): pseudoCure_1.0.0.tgz, r-oldrel (x86_64): not available |
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