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pseudoCure  

A Pseudo-Observations Approach for Analyzing Survival Data with a Cure Fraction
View on CRAN: Click here


Download and install pseudoCure package within the R console
Install from CRAN:
install.packages("pseudoCure")

Install from Github:
library("remotes")
install_github("cran/pseudoCure")

Install by package version:
library("remotes")
install_version("pseudoCure", "1.0.0")



Attach the package and use:
library("pseudoCure")
Maintained by
Sy Han (Steven) Chiou
[Scholar Profile | Author Map]
First Published: 2025-02-06
Latest Update: 2025-02-06
Description:
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.
How to cite:
Sy Han (Steven) Chiou (2025). pseudoCure: A Pseudo-Observations Approach for Analyzing Survival Data with a Cure Fraction. R package version 1.0.0, https://cran.r-project.org/web/packages/pseudoCure. Accessed 03 May. 2025.
Previous versions and publish date:
No previous versions
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View pseudoCure citation profile
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Complete documentation for pseudoCure
Functions, R codes and Examples using the pseudoCure R package
Full pseudoCure package functions and examples
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