Model of hidden heterogeneity in longitudinal data.
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.
Yashin
Anatoli I
AI
Center for Population Health and Aging, Duke University, Trent Hall, Room 002, Box 90408, Durham, NC 27708-0408, USA. aiy@duke.edu
Arbeev
Konstantin G
KG
Akushevich
Igor
I
Kulminski
Alexander
A
Akushevich
Lucy
L
Ukraintseva
Svetlana V
SV
D000375:Aging; D003627:Data Interpretation, Statistical; D006801:Humans; D008137:Longitudinal Studies; D015233:Models, Statistical; D014481:United States