Abstract
Survival analysis has recently gained popularity in many fields, particularly medical, social and
engineering. It is popularly used to analyze non-negative response variable describing the time to
an event of interest, usually a failure such as death, occurrence of complications and relapse, or
addressing the time to a successful event such as getting an employment or time to the first
marriage. In engineering field, survival analysis is also connected to reliability study. The nonnegative response variable is usually modeled either parametrically or non-parametrically, with
or without covariates in the selected model. Our focus in this article in on a parametric survival
model which not only incorporates fixed effect but also random effect associated with every
individual subject in the study, namely compound Poisson frailty model.