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pseudoCure


pseudoCure: Analysis of survival data with cure fraction and variable selection: A pseudo-observations approach

The pseudoCure package implements a pseudo-observation approach for survival data with a cure fraction. The modeling framework is based on the Cox proportional hazards mixture cure model and the bounded cumulative hazard model.

Installation

Install and load the package from GitHub using

> devtools::install_github("stc04003/pseudoCure")
> library(pseudoCure)
> packageVersion("pseudoCure")

Reference

Su, C.-L., Chiou, S., Lin, F.-C., and Platt, R. W. (2022) Analysis of survival data with cure fraction and variable selection: A pseudo-observations approach Statistical Methods in Medical Research, 31(11): 2037–2053.

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Version

Install

install.packages('pseudoCure')

Monthly Downloads

137

Version

1.0.0

License

GPL (>= 2)

Maintainer

Sy Han (Steven) Chiou

Last Published

February 6th, 2025

Functions in pseudoCure (1.0.0)

km

Kaplan-Meier estimate
plot.geelm

Plot method for 'geelm' objects
geelm

Generalized Estimating Equation with Gaussian family
pseudoCure-package

pseudoCure: A pseudo-observations approach for analyzing survival data with a cure fraction
pCure.control

Package options for pseudoCure
plot.pCure

Plot method for 'pCure' objects
mzTest

Maller-Zhou test
Teeth500

Dental data for illustration
pCure

Cure Rate Model with pseudo-observation approach