论文标题
疾病死亡数据的加速失败时间回归模型：一种脆弱的方法
An Accelerated Failure Time Regression Model for Illness-Death Data: A Frailty Approach
论文作者
论文摘要
这项工作为疾病函数遵循加速失败时间（AFT）模型提供了一个新的模型和估计程序，其中危险功能。共同的脆弱变量会导致受试者的失败时间之间的正依赖性，用于处理观察到的协变量给定的非末端和末端故障时间之间未观察到的依赖性。半参数最大似然估计过程是通过内核平滑的EM算法开发的，并通过加权引导程序估算方差。该模型是在现有的基于脆弱的疾病死亡模型的背景下提出的，强调了当前工作的贡献。使用拟议的和现有的疾病死亡模型分析鹿特丹肿瘤库的乳腺癌数据。结果根据新的图形拟合方法对比和评估。仿真结果和数据分析很好地证明了在疾病死亡框架下，共享脆弱变化与AFT回归模型的实际实用性。
This work presents a new model and estimation procedure for the illness-death survival data where the hazard functions follow accelerated failure time (AFT) models. A shared frailty variate induces positive dependence among failure times of a subject for handling the unobserved dependency between the non-terminal and the terminal failure times given the observed covariates. Semi-parametric maximum likelihood estimation procedure is developed via a kernel smoothed-aided EM algorithm, and variances are estimated by weighted bootstrap. The model is presented in the context of existing frailty-based illness-death models, emphasizing the contribution of the current work. The breast cancer data of the Rotterdam tumor bank are analyzed using the proposed and existing illness-death models. The results are contrasted and evaluated based on a new graphical goodness-of-fit procedure. Simulation results and data analysis nicely demonstrate the practical utility of the shared frailty variate with the AFT regression model under the illness-death framework.
