Model of Hidden Heterogeneity in Longitudinal Data

Overview

Journal Theor Popul Biol

Specialties Biology
Genetics
Reproductive Medicine

Date 2007 Nov 6

PMID 17977568

Citations 13

Authors

Anatoli I Yashin

Konstantin G Arbeev

Igor Akushevich

Alexander Kulminski

Lucy Akushevich

Svetlana V Ukraintseva

Affiliations

Soon will be listed here.

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.

Citing Articles

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Lin Y PLoS One. 2018; 13(3):e0193287.

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A genetic stochastic process model for genome-wide joint analysis of biomarker dynamics and disease susceptibility with longitudinal data.

He L, Zhbannikov I, Arbeev K, Yashin A, Kulminski A Genet Epidemiol. 2017; 41(7):620-635.

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Zhbannikov I, Arbeev K, Akushevich I, Stallard E, Yashin A BMC Bioinformatics. 2017; 18(1):125.

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How Genes Modulate Patterns of Aging-Related Changes on the Way to 100: Biodemographic Models and Methods in Genetic Analyses of Longitudinal Data.

Yashin A, Arbeev K, Wu D, Arbeeva L, Kulminski A, Kulminskaya I N Am Actuar J. 2016; 20(3):201-232.

PMID: 27773987 PMC: 5070546. DOI: 10.1080/10920277.2016.1178588.

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