Fitting Semi-Parametric Frailty Models with Poisson-Distributed Random Effects

다국어 초록 (Multilingual Abstract)

Frailty models with parametric or non-parametric baseline hazards have been widely used due to the consideration of heterogeneity or correlation in analysis of survival data. For the frailty distribution, a continuous distribution such as gamma-distributed frailty (or random effect) has been usually assumed. However, the frailty distribution is unobservable, and therefore the choice of frailty distribution should be based on general modelling considerations. Accordingly, a discrete-distributed frailty can be considered. In this paper, we propose a semi-parametric frailty model allowing non-parametric baseline hazard and Poisson distributed frailty. For the model fitting we present a profile likelihood-based estimation procedure. The proposed method is illustrated using a well-known practical survival data set. We find out that the Poisson frailty can be an useful alternative to non-PH survival data.

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