Evidence map›Paper›PMID 29978339›Full record

ArticleDemography2018

Bayesian Estimation of Age-Specific Mortality and Life Expectancy for Small Areas With Defective Vital Records.

Carl P Schmertmann, Marcos R Gonzaga

Abstract readComparative Study
PubMed Publisher
In one paragraph

Article in Demography, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

25 citing papers in PubMed.

  1. Article
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  4. Reliable event rates for disease mapping.Journal of official statistics · 2024
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  5. Article
  6. Article
  7. Article
  8. Article
  9. Spatial Inequities in Life Expectancy in Small Areas of Buenos Aires, Argentina 2015-2017.Journal of urban health : bulletin of the New York Academy of Medicine · 2023
    Article
  10. Article
  11. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Carl P SchmertmannCenter for Demography and Population Health, Florida State University, Tallahassee, FL, 32306-2240, USA. schmertmann@fsu.edu.
Marcos R GonzagaUniversidade Federal do Rio Grande do Norte, Natal, RN, Brazil.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

High sampling variability complicates estimation of demographic rates in small areas. In addition, many countries have imperfect vital registration systems, with coverage quality that varies significantly between regions. 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 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 underregistration and automatically producing measures of uncertainty. Bayesian estimates show that when mortality levels in small areas are compared, noise often dominates signal. Differences in local point estimates of life expectancy are often small relative to uncertainty, even for relatively large areas in a populous country like Brazil.

Indexed as

Bayes TheoremLife ExpectancyMortalitySmall-Area AnalysisAgedAge DistributionBrazilCensusesDemographyHumansMaleMiddle AgedVital StatisticsBayesian modelsData qualityMortalitySmall areas

Identifiers

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.