Analysis of Clustered Survival Data in the Presence of Cure with the Gompertz Distribution Model

摘要

We propose to analyze clustered survival data in presence of cure by a mixed-effect Gompertz model. Most literature for analyzing such data adopts the mixture approach which divides the population into two distinct groups being "susceptible" or "cured". We propose a different approach which directly models the overall distribution function by the Gompertz distribution with two parameters as functions of fixed and random covariates. An important feature of the proposed model is that "cure" is only a possibility rather than a deterministic status. Furthermore our model allows that cured individuals only exist in some covariate groups. The maximum likelihood estimates can be obtained via a Monte Carlo Expectation Maximization (MCEM) algorithm. The proposed method is illustrated through simulation studies and analysis of a real dataset.