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Decomposing Differences in Cohort Health Expectancy by Cause and Age With Longitudinal Data

Datos Bibliográficos

ID19230746
AutoresTao Sun (0000-0001-5509-0988, Renmin University of China), Huiping Zheng (0009-0006-1463-1841, Renmin University of China), Xiaojun Wang (0009-0006-0120-7275, Renmin University of China)
Año2026
Volumen63
Número3
Páginas925-953
Fecha de publicación2026-06-15
Peer ReviewedSí
Open AccessSí
TipoARTICLE
RevistaDemography (JOURNAL)
Identificadores de la revistaISSN: 0070-3370 • E-ISSN: 1533-7790
EditorialDuke University Press (PUBLISHER • US)
DOI10.1215/00703370-12654071
PMID42294953
OpenAlexW7164808230
IdiomaEN
Referencias citadas77

Highlights We propose a new method to decompose cohort health expectancy by age and cause. We develop a new attribution method for longitudinal data. This method handles interval censoring, semicompeting risks, and time-dependent covariates. We derive explicit formulas for stepwise decomposition of cohort health expectancy. We provide an R package and Shiny app to support use of the proposed method

Cohort · Cohort study · Expectancy theory · Health data · Life expectancy · Longitudinal data · Longitudinal study · Global Health Care Issues · Insurance, Mortality, Demography, Risk Management · Statistical Methods and Inference

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