Skip to main content
Journal cover image

Model of hidden heterogeneity in longitudinal data.

Publication ,  Journal Article
Yashin, AI; Arbeev, KG; Akushevich, I; Kulminski, A; Akushevich, L; Ukraintseva, SV
Published in: Theoretical population biology
February 2008

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.

Duke Scholars

Published In

Theoretical population biology

DOI

EISSN

1096-0325

ISSN

0040-5809

Publication Date

February 2008

Volume

73

Issue

1

Start / End Page

1 / 10

Related Subject Headings

  • United States
  • Models, Statistical
  • Longitudinal Studies
  • Humans
  • Evolutionary Biology
  • Data Interpretation, Statistical
  • Aging
  • 4901 Applied mathematics
  • 3104 Evolutionary biology
  • 3103 Ecology
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Yashin, A. I., Arbeev, K. G., Akushevich, I., Kulminski, A., Akushevich, L., & Ukraintseva, S. V. (2008). Model of hidden heterogeneity in longitudinal data. Theoretical Population Biology, 73(1), 1–10. https://doi.org/10.1016/j.tpb.2007.09.001
Yashin, Anatoli I., Konstantin G. Arbeev, Igor Akushevich, Alexander Kulminski, Lucy Akushevich, and Svetlana V. Ukraintseva. “Model of hidden heterogeneity in longitudinal data.Theoretical Population Biology 73, no. 1 (February 2008): 1–10. https://doi.org/10.1016/j.tpb.2007.09.001.
Yashin AI, Arbeev KG, Akushevich I, Kulminski A, Akushevich L, Ukraintseva SV. Model of hidden heterogeneity in longitudinal data. Theoretical population biology. 2008 Feb;73(1):1–10.
Yashin, Anatoli I., et al. “Model of hidden heterogeneity in longitudinal data.Theoretical Population Biology, vol. 73, no. 1, Feb. 2008, pp. 1–10. Epmc, doi:10.1016/j.tpb.2007.09.001.
Yashin AI, Arbeev KG, Akushevich I, Kulminski A, Akushevich L, Ukraintseva SV. Model of hidden heterogeneity in longitudinal data. Theoretical population biology. 2008 Feb;73(1):1–10.
Journal cover image

Published In

Theoretical population biology

DOI

EISSN

1096-0325

ISSN

0040-5809

Publication Date

February 2008

Volume

73

Issue

1

Start / End Page

1 / 10

Related Subject Headings

  • United States
  • Models, Statistical
  • Longitudinal Studies
  • Humans
  • Evolutionary Biology
  • Data Interpretation, Statistical
  • Aging
  • 4901 Applied mathematics
  • 3104 Evolutionary biology
  • 3103 Ecology