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 |
| 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:
Downloads:
Linking:
Please use the canonical form
https://CRAN.R-project.org/package=pseudoCure
to link to this page.