The R Journal: accepted article

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penPHcure: Variable Selection in Proportional Hazards Cure Model with Time-Varying Covariates PDF download
Alessandro Beretta and Cédric Heuchenne

Abstract We describe the penPHcure R package, which implements the semi-parametric proportional hazards (PH) cure model of Sy and Taylor (2000) extended to time-varying covariates and the variable selection technique based on its SCAD-penalized likelihood proposed by Beretta and Heuchenne (2019a). In survival analysis, cure models are a useful tool when a fraction of the population is likely to be immune from the event of interest. They can separate the effects of certain factors on the probability to be susceptible and on the time until the occurrence of the event. Moreover, the penPHcure package allows the user to simulate data from a PH cure model, where the event-times are generated on a continuous scale from a piecewise exponential distribution conditional on time-varying covariates, with a method similar to Hendry (2014). We present the results of a simulation study to assess the finite sample performance of the methodology and we illustrate the functionalities of the penPHcure package using criminal recidivism data.

Received: ; online 2021-06-21
CRAN packages: penPHcure, flexsurvcure, flexsurv, nltm, smcure, spduration, survival, RcmdrPlugin.survival
CRAN Task Views implied by cited CRAN packages: Survival, ClinicalTrials, Distributions, Econometrics, SocialSciences


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@article{RJ-2021-061,
  author = {Alessandro Beretta and Cédric Heuchenne},
  title = {{penPHcure: Variable Selection in Proportional Hazards Cure
          Model with Time-Varying Covariates}},
  year = {2021},
  journal = {{The R Journal}},
  doi = {10.32614/RJ-2021-061},
  url = {https://journal.r-project.org/archive/2021/RJ-2021-061/index.html}
}