标题： MEGH：聚类生存数据的一类参数广义风险模型 显示英文标题

标题： MEGH: A parametric class of general hazard models for clustered survival data

摘要： 在生存数据分 析的许多应用中，个体接受治疗的医学中心不同，或者归属于由地理或行政区域定义的不同群集。 此类数据的分析需要考虑群集间的变异性。忽略这种变异性会在分析中引入不切实际的假设，并可能影响统计模型的推断。 我们开发了一种新的参数混合效应广义危险率（MEGH）模型，该模型特别适合于聚集生存数据的分析。 所提出的结构推广了混合效应比例风险（MEPH）和混合效应加速失效时间（MEAFT）等结构，以及其他结构，这些结构是MEGH结构的特例。 我们为MEGH模型的一般子类开发了一种基于似然的方法来估计参数，该方法已在我们的 R 包{\tt MEGH}中实现。 我们提出了诊断工具来评估所提出的MEGH模型中的随机效应及其分布假设。 我们通过理论研究、模拟研究以及白血病的真实数据分析，研究了MEGH模型的性能。 显示英文摘要

摘要： 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.