frailtypack: a computer program for the analysis of correlated failure time data using penalized likelihood estimation

Correlated survival outcomes occur quite frequently in the biomedical research. Available software is limited, particularly if we wish to obtain smoothed estimate of the baseline hazard function in the context of random effects model for correlated data. The main objective of this paper is to describe an R package called frailtypack that can be used for estimating the parameters in a shared gamma frailty model with possibly right-censored, left-truncated stratified survival data using penalized likelihood estimation. Time-dependent structure for the explanatory variables and/or extension of the Cox regression model to recurrent events are also allowed. This program can also be used simply to obtain directly a smooth estimate of the baseline hazard function. To illustrate the program we used two data sets, one with clustered survival times, the other one with recurrent events, i.e., the rehospitalizations of patients diagnosed with colorectal cancer. We show how to fit the model with recurrent events and time-dependent covariates using Andersen-Gill approach.