A Flexible Bayesian Model for Estimating Subnational Mortality.
Reliable subnational mortality estimates are essential in the study of health inequalities within a country. One of the difficulties in producing such estimates is the presence of small populations among which the stochastic variation in death counts is relatively high, and thus the underlying morta...
| Published in: | Demography (Springer Nature) Vol. 54; no. 6; pp. 2025 - 2042 |
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| Main Authors: | , , |
| Format: | journal article |
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Springer Nature
Dec2017
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| Subjects: | |
| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=126418616&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 126418616 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 00703370 DEM jtl: Demography (Springer Nature) issn: 00703370 maglogo: N pubinfo: dt: Dec2017 vid: 54 iid: 6 pid: 237 pub: Springer Nature artinfo: ui: 126418616 10.1007/s13524-017-0618-7 ppf: 2025 ppct: 17 formats: fmt: @attributes: type: P size: 1.1MB tig: atl: A Flexible Bayesian Model for Estimating Subnational Mortality. aug: au: Alexander, Monica Zagheni, Emilio Barbieri, Magali affil: Department of Demography , University of California , Berkeley, 2232 Piedmont Avenue Berkeley 94720-2120 USA Department of Sociology , University of Washington , Seattle, 211 Savery Hall, Box 353340 Seattle 98195-3340 USA su: France United States Mortality Health equity Computer simulation Demography Life expectancy Population geography Bayesian analysis Stochastic processes Cluster analysis (Statistics) Poisson distribution Probability theory Statistical models sug: subj: Mortality Health equity Computer simulation Demography Life expectancy Population geography France United States Bayesian analysis Stochastic processes Cluster analysis (Statistics) Poisson distribution Probability theory Statistical models keyword: Bayesian hierarchical model Principal components Subnational estimation Bayesian hierarchical model Principal components Subnational estimation ab: Reliable subnational mortality estimates are essential in the study of health inequalities within a country. One of the difficulties in producing such estimates is the presence of small populations among which the stochastic variation in death counts is relatively high, and thus the underlying mortality levels are unclear. We present a Bayesian hierarchical model to estimate mortality at the subnational level. The model builds on characteristic age patterns in mortality curves, which are constructed using principal components from a set of reference mortality curves. Information on mortality rates are pooled across geographic space and are smoothed over time. Testing of the model shows reasonable estimates and uncertainty levels when it is applied both to simulated data that mimic U.S. counties and to real data for French départements. The model estimates have direct applications to the study of subregional health patterns and disparities. pubtype: Academic Journal doctype: journal article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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