论文标题
共同的脆弱方法用于复杂生存数据：对最新进展的评论
Shared Frailty Methods for Complex Survival Data: A Review of Recent Advances
论文作者
论文摘要
依赖生存数据在许多情况下出现。一种环境是聚类的生存数据，其中收集了在家庭或医疗中心等集群上的生存数据。当每个人都记录了多个生存时间时，还会出现依赖生存数据。脆弱的模型是处理此类数据的一种常见方法。在脆弱的模型中，依赖性是根据随机效应（称为脆弱的）表示的。 COX比例危害模型和加速故障时间模型都使用了脆弱的模型。本文回顾了各种环境中脆弱模型领域的最新发展。在每种情况下，我们都提供详细的模型描述，假设，可用估计方法和R软件包。
Dependent survival data arise in many contexts. One context is clustered survival data, where survival data are collected on clusters such as families or medical centers. Dependent survival data also arise when multiple survival times are recorded for each individual. Frailty models is one common approach to handle such data. In frailty models, the dependence is expressed in terms of a random effect, called the frailty. Frailty models have been used with both Cox proportional hazards model and the accelerated failure time model. This paper reviews recent developments in the area of frailty models in a variety of settings. In each setting we provide a detailed model description, assumptions, available estimation methods, and R packages.
