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Asymptotic theory for the Cox semi-Markov illness-death model

机译:考克斯半马氏疾病死亡模型的渐近理论

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Irreversible illness-death models are used to model disease processes and in cancer studies to model disease recovery. In most applications, a Markov model is assumed for the multistate model. When there are covariates, a Cox (1972, J Roy Stat Soc Ser B 34:187-220) model is used to model the effect of covariates on each transition intensity. Andersen et al. (2000, Stat Med 19:587-599) proposed a Cox semi-Markov model for this problem. In this paper, we study the large sample theory for that model and provide the asymptotic variances of various probabilities of interest. A Monte Carlo study is conducted to investigate the robustness and efficiency of Markov/Semi-Markov estimators. A real data example from the PROVA (1991, Hepatology 14:1016-1024) trial is used to illustrate the theory.
机译:不可逆病死模型用于模型化疾病过程,在癌症研究中用于模型化疾病恢复。在大多数应用中,多状态模型被假定为马尔可夫模型。当存在协变量时,使用Cox(1972,J Roy Stat Soc Ser B 34:187-220)模型对每个过渡强度对协变量的影响进行建模。 Andersen等。 (2000,Stat Med 19:587-599)提出了用于该问题的Cox半马尔可夫模型。在本文中,我们研究了该模型的大样本理论,并提供了各种感兴趣概率的渐近方差。进行了蒙特卡洛研究,以研究Markov / Semi-Markov估计量的鲁棒性和效率。来自PROVA(1991,Hepatology 14:1016-1024)试验的真实数据示例用于说明该理论。

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