Evidence map›Paper›PMID 39323985›Full record

ArticleThe annals of applied statistics2024

A BAYESIAN HIERARCHICAL SMALL AREA POPULATION MODEL ACCOUNTING FOR DATA SOURCE SPECIFIC METHODOLOGIES FROM AMERICAN COMMUNITY SURVEY, POPULATION ESTIMATES PROGRAM, AND DECENNIAL CENSUS DATA.

Emily N Peterson, Rachel C Nethery, Tullia Padellini, Jarvis T Chen, Brent A Coull, Frédéric B Piel, Jon Wakefield, Marta Blangiardo, Lance A Waller

Abstract read
In one paragraph

Article in The annals of applied statistics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
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

9 authors.

Emily N PetersonDepartment of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University.
Rachel C NetheryDepartment of Biostatistics, Harvard T.H. Chan School of Public Health.
Tullia PadelliniDepartment of Epidemiology and Biostatistics, School of Public Health, Imperial College London.
Jarvis T ChenDepartment of Biostatistics, Harvard T.H. Chan School of Public Health.
Brent A CoullDepartment of Biostatistics, Harvard T.H. Chan School of Public Health.
Frédéric B PielDepartment of Epidemiology and Biostatistics, School of Public Health, Imperial College London.
Jon WakefieldDepartment of Biostatistics, School of Public Health, University of Washington.
Marta BlangiardoDepartment of Epidemiology and Biostatistics, School of Public Health, Imperial College London.
Lance A WallerDepartment of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University.

Funding

Improving statistical methods for small area estimates of public health indicators and demographic characteristicsR01HD092580 · NICHD · EMORY UNIVERSITY · PI Lance A Waller · 2018 to 2026
$2.3M
NICHD NIH HHS R01 HD092580
6 · The paper itself

Abstract

Small area population counts are necessary for many epidemiological studies, yet their quality and accuracy are often not assessed. In the United States, small area population counts are published by the United States Census Bureau (USCB) in the form of the decennial census counts, intercensal population projections (PEP), and American Community Survey (ACS) estimates. Although there are significant relationships between these three data sources, there are important contrasts in data collection, data availability, and processing methodologies such that each set of reported population counts may be subject to different sources and magnitudes of error. Additionally, these data sources do not report identical small area population counts due to post-survey adjustments specific to each data source. Consequently, in public health studies, small area disease/mortality rates may differ depending on which data source is used for denominator data. To accurately estimate annual small area population counts

Indexed as

American Community SurveyBayesian methodsdecennial censussampling and nonsampling errorsSmall area population estimates

Identifiers

PMID39323985
PMCPMC11423836

What OpenQuestion holds

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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.