| Improving ecological inference using individual-level data. | |
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MedLine Citation:
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PMID: 16217847 Owner: NLM Status: MEDLINE |
Abstract/OtherAbstract:
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In typical small-area studies of health and environment we wish to make inference on the relationship between individual-level quantities using aggregate, or ecological, data. Such ecological inference is often subject to bias and imprecision, due to the lack of individual-level information in the data. Conversely, individual-level survey data often have insufficient power to study small-area variations in health. Such problems can be reduced by supplementing the aggregate-level data with small samples of data from individuals within the areas, which directly link exposures and outcomes. We outline a hierarchical model framework for estimating individual-level associations using a combination of aggregate and individual data. We perform a comprehensive simulation study, under a variety of realistic conditions, to determine when aggregate data are sufficient for accurate inference, and when we also require individual-level information. Finally, we illustrate the methods in a case study investigating the relationship between limiting long-term illness, ethnicity and income in London. |
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Authors:
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Christopher Jackson; Nicky Best; Sylvia Richardson |
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Publication Detail:
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Type: Journal Article; Research Support, Non-U.S. Gov't |
Journal Detail:
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Title: Statistics in medicine Volume: 25 ISSN: 0277-6715 ISO Abbreviation: Stat Med Publication Date: 2006 Jun |
Date Detail:
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Created Date: 2006-05-17 Completed Date: 2006-10-31 Revised Date: 2006-11-15 |
Medline Journal Info:
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Nlm Unique ID: 8215016 Medline TA: Stat Med Country: England |
Other Details:
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Languages: eng Pagination: 2136-59 Citation Subset: IM |
Copyright Information:
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Copyright (c) 2005 John Wiley & Sons, Ltd. |
Affiliation:
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Department of Epidemiology and Public Health, Imperial College School of Medicine, London, U.K. chris.jackson@imperial.ac.uk |
Export Citation:
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| MeSH Terms | |
Descriptor/Qualifier:
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Data Interpretation, Statistical* Environment* Humans London Models, Statistical* Multivariate Analysis Social Change* Socioeconomic Factors |
From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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