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

机译:使用Gompertz分布模型对存在治愈的聚类生存数据进行分析

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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.
机译:我们建议通过混合效应Gompertz模型分析存在治愈的聚集生存数据。用于分析此类数据的大多数文献都采用混合方法,将人口分为“易感”或“治愈”两个不同的群体。我们提出了一种不同的方法,该方法通过Gompertz分布直接建模总体分布函数,其中有两个参数作为固定和随机协变量的函数。提出的模型的一个重要特征是“治愈”仅是一种可能性,而不是确定性状态。此外,我们的模型允许治愈的个体仅存在于某些协变量组中。可以通过蒙特卡洛期望最大化(MCEM)算法获得最大似然估计。通过仿真研究和对真实数据集的分析说明了所提出的方法。

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