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frailtypack : An R Package for the Analysis of Correlated Survival Data with Frailty Models Using Penalized Likelihood Estimation or Parametrical Estimation

2012; Foundation for Open Access Statistics; Volume: 47; Issue: 4 Linguagem: Inglês

10.18637/jss.v047.i04

1548-7660

Virginie Rondeau, Yassin Mazroui, Juan R. González,

Health Systems, Economic Evaluations, Quality of Life

Frailty models are very useful for analysing correlated survival data, when observations are clustered into groups or for recurrent events. The aim of this article is to present the new version of an R package called frailtypack. This package allows to fit Cox models and four types of frailty models (shared, nested, joint, additive) that could be useful for several issues within biomedical research. It is well adapted to the analysis of recurrent events such as cancer relapses and/or terminal events (death or lost to follow-up). The approach uses maximum penalized likelihood estimation. Right-censored or left-truncated data are considered. It also allows stratification and time-dependent covariates during analysis.