Modelling failure-time associations in data with multiple levels of clustering
多层聚类数据中失效时间关联的建模AI 解读 ↓
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AI 根据所提供的论文材料归类：摘要研究多层聚类生存数据的依赖模型，聚类与 copula 本身不足以归入所列网络或分布效应方向。
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多层聚类数据中失效时间关联的建模
- 研究问题
- 当失效时间在家庭、村庄等不同层级存在关联时，如何建立同时描述多层依赖并保留单层模型联系的分布模型？
- 方法与思路
- 作者递归嵌套单变量脆弱性型分布以构造生存函数，由此确定各二元边际的阿基米德 copula 形式。
- 材料陈述的贡献
- 摘要提出可容纳多层聚类的模型族，称单层情形退化为单变量脆弱性模型，并讨论性质及边际风险回归应用。
- 阅读关注点
- 应核对嵌套结构形成有效联合分布的条件、不同层级关联的参数解释，以及与多变量脆弱性模型的具体差别。
- 阅读边界
- 所据索引摘要未注明稿件版本，也未提供参数约束、估计程序或实证结果；不能据此判断模型的拟合与识别表现。
原文摘要
In recent years substantial research has been devoted to developing failure-time methodology which accounts for possible dependency between observations. An example is the univariate frailty model (Vaupel, Manton & Stallard, 1979), which incorporates an exchangeable dependence structure by the inclusion of cluster-specific random effects. In some studies it may be reasonable to expect more than one level of within-cluster association: for instance, association between a parent and child versus that between two siblings in studies of familial disease aggregation, or association between two village residents who live in different households versus that between residents of the same household in intervention studies. We propose a family of distributional models for failure-time data that accounts for multiple levels of clustering and reduces in the case of a single clustering level to a univariate frailty model. The resulting survival functions are constructed by a recursive nesting of univariate frailty-type distributions through which archimedean copula forms are determined for all bivariate margins. Properties of the proposed model are developed, illustrated and briefly contrasted with multivariate frailty model properties. In conclusion, we outline the application of our model to marginal risk regression problems.