penPHcure: Variable Selection in Proportional Hazards Cure Model with Time-Varying Covariates

Alessandro Beretta and Cédric Heuchenne
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Cédric Heuchenne: Université catholique de Louvain, LIDAM/ISBA, Belgium

No 2021036, LIDAM Reprints ISBA from Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA)

Abstract: We describe the penPHcure R package, which implements the semiparametric proportionalhazards (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 of being 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 illustrate the functionalities of the penPHcure package using criminal recidivism data.

Pages: 14
Date: 2021-06-01
Note: In: The R Journal, 2021, vol. 13/1, p. 116-129
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