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Joint Analysis of Health Histories, Physiological State, and Survival

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  • ANATOLY I. YASHIN
  • IGOR AKUSHEVICH
  • KONSTANTIN G. ARBEEV
  • ALEXANDER KULMINSKI
  • SVETLANA UKRAINTSEVA

Abstract

Data on individual health histories, age trajectories of physiological or biological variables, and mortality allow for the study of the joint evolution of health and physiological states and their effects on mortality. Individual health and physiological trajectories are described using a stochastic process with two mutually-dependent continuous and jumping components. The parameters of this process and mortality rate are identified from the data in which the continuous component is measured in discrete times, and transitions of jumping process are observed.

Suggested Citation

  • Anatoly I. Yashin & Igor Akushevich & Konstantin G. Arbeev & Alexander Kulminski & Svetlana Ukraintseva, 2011. "Joint Analysis of Health Histories, Physiological State, and Survival," Mathematical Population Studies, Taylor & Francis Journals, vol. 18(4), pages 207-233, October.
  • Handle: RePEc:taf:mpopst:v:18:y:2011:i:4:p:207-233
    DOI: 10.1080/08898480.2011.614486
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    References listed on IDEAS

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    1. Anatoli Yashin & Ivan Iachine & Kirill Andreev & Ulla Larsen, 1998. "Multistate models of postpartum infecundity, fecundability and sterility by age and parity: Methodological issues," Mathematical Population Studies, Taylor & Francis Journals, vol. 7(1), pages 51-78.
    2. Anatoli Yashin & Ivan Iachine & Alexander Begun, 2000. "Mortality modeling: A review," Mathematical Population Studies, Taylor & Francis Journals, vol. 8(4), pages 305-332.
    3. Yashin, Anatoli I. & Arbeev, Konstantin G. & Akushevich, Igor & Kulminski, Alexander & Akushevich, Lucy & Ukraintseva, Svetlana V., 2008. "Model of hidden heterogeneity in longitudinal data," Theoretical Population Biology, Elsevier, vol. 73(1), pages 1-10.
    4. I. Akushevich & A. Kulminski & K. G. Manton, 2005. "Life Tables with Covariates: Dynamic Model for Nonlinear Analysis of Longitudinal Data," Mathematical Population Studies, Taylor & Francis Journals, vol. 12(2), pages 51-80.
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