Literature DB >> 12286785

Methods for combining ancillary data in stochastic compartment models of cancer mortality: generalization of heterogeneity models.

K G Manton, G Lowrimore, A Yashin.   

Abstract

"We present a mortality model where nationally representative survey data on risk factor distributions are combined with data on cohort mortality rates to increase information, i.e., a fixed marginal risk factor distribution is combined with a cohort model representing unobserved individual risk heterogeneity. The model is applied to lung cancer mortality in nine U.S. white male cohorts aged 30 to 70 in 1950 and followed 38 years. Estimates of the cohort specific proportions of smokers were made from the National Health Interview Survey. Comparisons are made for models with different patterns of changes with age of individual heterogeneity." (SUMMARY IN FRE) excerpt

Entities:  

Keywords:  Americas; Behavior; Biology; Cancer; Cohort Analysis; Comparative Studies; Data Collection; Data Sources; Demographic Factors; Developed Countries; Diseases; Heterogeneity; Mathematical Model; Models, Theoretical; Mortality; Neoplasms; North America; Northern America; Physiology; Population; Population Characteristics; Population Dynamics; Pulmonary Effects; Research Methodology; Risk Factors; Smoking; Studies; United States

Mesh:

Year:  1993        PMID: 12286785     DOI: 10.1080/08898489309525365

Source DB:  PubMed          Journal:  Math Popul Stud        ISSN: 0889-8480            Impact factor:   0.720


  1 in total

1.  Indirect estimation of a discrete-state discrete-time model using secondary data analysis of regression data.

Authors:  Deanna J M Isaman; Jacob Barhak; Wen Ye
Journal:  Stat Med       Date:  2009-07-20       Impact factor: 2.373

  1 in total

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