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Bayesian estimation of age-specific mortality and life expectancy for small areas with defective vital records

Author

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  • Schmertmann, Carl

    (Florida State University)

  • Gonzaga, Marcos Roberto
Abstract
We develop a Bayesian regression model for small-area mortality schedules that simultaneously addresses the problems of small local samples and underreporting of deaths. We combine a relational model for mortality schedules with probabilistic prior information on death registration coverage – derived from demographic estimation techniques such as Death Distribution Methods, and from field audits done by public health experts. We test the model on small-area data from Brazil. Incorporating external estimates of vital registration coverage though priors improves small-area mortality estimates by accounting for under-registration, and by automatically producing measures of uncertainty.

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  • Schmertmann, Carl & Gonzaga, Marcos Roberto, 2018. "Bayesian estimation of age-specific mortality and life expectancy for small areas with defective vital records," SocArXiv syzwx, Center for Open Science.
    • Handle: RePEc:osf:socarx:syzwx
    DOI: 10.31219/osf.io/syzwx
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    References listed on IDEAS

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    Cited by:

    1. Emerson Baptista & Bernardo Lanza Queiroz, 2019. "The relation between cardiovascular mortality and development: Study for small areas in Brazil, 2001–2015," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 41(51), pages 1437-1452.
    2. Queiroz, Bernardo L & Gonzaga, Marcos Roberto & Nogales, Ana Maria & Torrente, Bruno & de Abreu, Daisy Maria Xavier, 2019. "Life expectancy, adult mortality and completeness of death counts in Brazil and regions: comparative analysis of IHME, IBGE and other researchers estimates of levels and trends," OSF Preprints pj3sx, Center for Open Science.
    3. Carl Schmertmann, 2021. "D-splines: Estimating rate schedules using high-dimensional splines with empirical demographic penalties," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 44(45), pages 1085-1114.
    4. Qian Lu & Katja Hanewald & Xiaojun Wang, 2021. "Subnational Mortality Modelling: A Bayesian Hierarchical Model with Common Factors," Risks, MDPI, vol. 9(11), pages 1-21, November.
    5. Gonzaga, Marcos Roberto & Queiroz, Bernardo L & Monteiro da Silva, José H C & Lima, Everton & Júnio, Walter P. Silva & DIOGENES, VICTOR HUGO DIAS & Flores-Ortiz, Renzo & da Costa, Lilia Carolina Carne, 2022. "Estimation and projection of probabilistic age- and sex-specific mortality rates across Brazilian municipalities between 2010 and 2030," OSF Preprints egrc9, Center for Open Science.
    6. Emerson A. Baptista & Bernardo L. Queiroz & Everton E. C. Lima, 2022. "Regional COVID-19 mortality in Brazil by age," Vienna Yearbook of Population Research, Vienna Institute of Demography (VID) of the Austrian Academy of Sciences in Vienna, vol. 20(1), pages 349-365.

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