论文标题
MEGH：用于聚类生存数据的一般危害模型的参数类别
MEGH: A parametric class of general hazard models for clustered survival data
论文作者
论文摘要
在生存数据分析的许多应用中，个人在不同的医疗中心进行处理或属于由地理或行政区域定义的不同集群。对此类数据的分析需要考虑集群间的可变性。忽略这种可变性会在分析中施加不切实际的假设，并可能影响统计模型的推断。我们开发了一种新型的参数混合效应一般危害（MEGH）模型，该模型特别适合分析聚类的生存数据。所提出的结构将混合效应比例危害（MEPH）和混合效应加速失败时间（MEAFT）结构以及其他结构以及其他结构（作为MEGH结构的特殊情况获得）。我们在MEGH模型的一般子类中开发了一种基于可能性的算法，用于参数估计，该算法在我们的R软件包{\ tt Megh}中实现。我们建议在提出的MEGH模型中评估随机效应及其分布假设的诊断工具。我们使用理论和仿真研究以及白血病的真实数据应用研究了MEGH模型的性能。
In many applications of survival data analysis, the individuals are treated in different medical centres or belong to different clusters defined by geographical or administrative regions. The analysis of such data requires accounting for between-cluster variability. Ignoring such variability would impose unrealistic assumptions in the analysis and could affect the inference on the statistical models. We develop a novel parametric mixed-effects general hazard (MEGH) model that is particularly suitable for the analysis of clustered survival data. The proposed structure generalises the mixed-effects proportional hazards (MEPH) and mixed-effects accelerated failure time (MEAFT) structures, among other structures, which are obtained as special cases of the MEGH structure. We develop a likelihood-based algorithm for parameter estimation in general subclasses of the MEGH model, which is implemented in our R package {\tt MEGH}. We propose diagnostic tools for assessing the random effects and their distributional assumption in the proposed MEGH model. We investigate the performance of the MEGH model using theoretical and simulation studies, as well as a real data application on leukemia.
