Peng Yingwei, Zhang Jiajia
Department of Community Health and Epidemiology, Queen's University, Kingston, Ont., Canada K7L 3N6.
Stat Med. 2008 Nov 10;27(25):5177-94. doi: 10.1002/sim.3358.
Mixture cure frailty model has been proposed to analyze censored survival data with a cured fraction and unobservable information among the uncured patients. Different from a usual mixture cure model, the frailty model is employed to model the latency component in the mixture cure frailty model. In this paper, we extend the mixture cure frailty model by incorporating covariates into both the cure rate and the latency distribution parts of the model and propose a semiparametric estimation method for the model. The Expectation Maximization (EM) algorithm and the multiple imputation method are employed to estimate parameters of interest. In the simulation study, we show that both estimation methods work well. To illustrate, we apply the model and the proposed methods to a data set of failure times from bone marrow transplant patients.
混合治愈脆弱模型已被提出用于分析具有治愈比例以及未治愈患者中不可观测信息的删失生存数据。与通常的混合治愈模型不同，脆弱模型被用于对混合治愈脆弱模型中的潜伏期部分进行建模。在本文中，我们通过将协变量纳入模型的治愈率和潜伏期分布部分来扩展混合治愈脆弱模型，并提出了该模型的半参数估计方法。采用期望最大化（EM）算法和多重填补方法来估计感兴趣的参数。在模拟研究中，我们表明这两种估计方法都表现良好。为了说明，我们将该模型和所提出的方法应用于一组来自骨髓移植患者的失败时间数据集。
