Assessing community variation and randomness in public health indicators

Stephan Arndt; Laura Acion; Kristin Caspers; Ousmane Diallo

doi:10.1186/1478-7954-9-3

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Assessing community variation and randomness in public health indicators

Journal article

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Peer reviewed

Assessing community variation and randomness in public health indicators

Stephan Arndt, Laura Acion, Kristin Caspers and Ousmane Diallo

Population health metrics, Vol.9(1), pp.3-3

02/02/2011

DOI: 10.1186/1478-7954-9-3

PMCID: PMC3045330

PMID: 21288354

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Abstract

Background: Evidence-based health indicators are vital to needs-based programming and epidemiological planning. Agencies frequently make programming funds available to local jurisdictions based on need. The use of objective indicators to determine need is attractive but assumes that selection of communities with the highest indicators reflects something other than random variability from sampling error. Methods: The authors compare the statistical performance of two heterogeneity measures applied to community differences that provide tests for randomness and measures of the percentage of true community variation, as well as estimates of the true variation. One measure comes from the meta-analysis literature and the other from the simple Pearson chi-square statistic. Simulations of populations and an example using real data are provided. Results: The measure based on the simple chi-square statistic seems superior, offering better protection against Type I errors and providing more accurate estimates of the true community variance. Conclusions: The heterogeneity measure based on Pearson's χ2 should be used to assess indices. Methods for improving poor indices are discussed.

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Details

Title: Subtitle: Assessing community variation and randomness in public health indicators
Creators: Stephan Arndt - University of Iowa, Biostatistics
Laura Acion - University of Iowa, Psychiatry
Kristin Caspers - Iowa Consortium for Substance Abuse Research and Evaluation, 100 Oakdale Campus M308 OH, University of Iowa, Iowa City, Iowa 52245-5000, USA
Ousmane Diallo - Iowa Department of Public Health, Des Moines, Iowa, USA
Resource Type: Journal article
Publication Details: Population health metrics, Vol.9(1), pp.3-3
DOI: 10.1186/1478-7954-9-3
PMID: 21288354
PMCID: PMC3045330
NLM abbreviation: Popul Health Metr
ISSN: 1478-7954
eISSN: 1478-7954
Publisher: BioMed Central
Language: English
Date published: 02/02/2011
Academic Unit: Psychiatry; Epidemiology; Biostatistics; Nursing; Injury Prevention Research Center
Record Identifier: 9984130701202771

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