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纵向数据中的隐藏异质性模型。

Model of hidden heterogeneity in longitudinal data.

作者信息

Yashin Anatoli I, Arbeev Konstantin G, Akushevich Igor, Kulminski Alexander, Akushevich Lucy, Ukraintseva Svetlana V

机构信息

Center for Population Health and Aging, Duke University, Trent Hall, Room 002, Box 90408, Durham, NC 27708-0408, USA.

出版信息

Theor Popul Biol. 2008 Feb;73(1):1-10. doi: 10.1016/j.tpb.2007.09.001. Epub 2007 Sep 18.

Abstract

Variables measured in longitudinal studies of aging and longevity do not exhaust the list of all factors affecting health and mortality transitions. Unobserved factors generate hidden variability in susceptibility to diseases and death in populations and in age trajectories of longitudinally measured indices. Effects of such heterogeneity can be manifested not only in observed hazard rates but also in average trajectories of measured indices. Although effects of hidden heterogeneity on observed mortality rates are widely discussed, their role in forming age patterns of other aging-related characteristics (average trajectories of physiological state, stress resistance, etc.) is less clear. We propose a model of hidden heterogeneity to analyze its effects in longitudinal data. The approach takes the presence of hidden heterogeneity into account and incorporates several major concepts currently developing in aging research (allostatic load, aging-associated decline in adaptive capacity and stress-resistance, age-dependent physiological norms). Simulation experiments confirm identifiability of model's parameters.

摘要

在衰老和长寿纵向研究中所测量的变量并未穷尽所有影响健康和死亡转变的因素。未观测到的因素在人群对疾病和死亡的易感性以及纵向测量指标的年龄轨迹中产生了隐藏的变异性。这种异质性的影响不仅可以体现在观测到的风险率中,还可以体现在测量指标的平均轨迹中。尽管隐藏异质性对观测到的死亡率的影响已得到广泛讨论,但其在形成其他与衰老相关特征(生理状态、抗应激能力等的平均轨迹)的年龄模式中的作用尚不清楚。我们提出了一个隐藏异质性模型来分析其在纵向数据中的影响。该方法考虑了隐藏异质性的存在,并纳入了目前衰老研究中正在发展的几个主要概念(应激负荷、与衰老相关的适应能力和抗应激能力下降、年龄依赖性生理规范)。模拟实验证实了模型参数的可识别性。

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