Linked Life Data

8568421

Source:http://linkedlifedata.com/resource/pubmed/id/8568421

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
1
pubmed:dateCreated
1996-3-5
pubmed:abstractText
A model of human health history and aging, based on a multivariate stochastic process with both continuous diffusion and discrete jump components, is presented. Discrete changes generate non-Gaussian diffusion with time varying continuous state distributions. An approach to calculating transition rates in dynamically heterogeneous populations, which generalizes the conditional averaging of hazard rates done in "fixed frailty" population models, is presented to describe health processes with multiple jumps. Conditional semi-invariants are used to approximate the conditional p.d.f. of the unobserved health history components. This is useful in analyzing the age dependence of mortality and health changes at advanced age (e.g., 95+) where homeostatic controls weaken, and physiological dynamics and survival manifest nonlinear behavior.
pubmed:grant
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:issn
0303-6812
pubmed:author
pubmed:issnType
Print
pubmed:volume
34
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
1-16
pubmed:dateRevised
2007-11-14
pubmed:meshHeading
pubmed:year
1995
pubmed:articleTitle
The effects of health histories on stochastic process models of aging and mortality.
pubmed:affiliation
Institute of Community Health, Odense University, Denmark.
pubmed:publicationType
Journal Article, Research Support, U.S. Gov't, P.H.S.