| Regression of area mortality rates on explanatory variables: what weighting is appropriate? | |
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MedLine Citation:
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PMID: 12157995 Owner: PIP Status: MEDLINE |
Abstract/OtherAbstract:
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"One can often gain insight into the aetiology of a disease by relating mortality rates in different areas to explanatory variables. Multiple regression techniques are usually employed, but unweighted least squares may be inappropriate if the areas vary in population size. Also, a fully weighted regression, with weights inversely proportional to binomial sampling variances, is usually too extreme. This paper proposes an intermediate solution via maximum likelihood which takes account of three sources of variation in death rates: sampling error, explanatory variables and unexplained differences between areas. The method is also adapted for logit (death rates), standardized mortality ratios (SMRs) and log (SMRs). Two [United Kingdom] examples are presented." |
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Authors:
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S J Pocock; D G Cook; S A Beresford |
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Publication Detail:
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Type: Journal Article |
Journal Detail:
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Title: Journal of the Royal Statistical Society. Series C, Applied statistics Volume: 30 ISSN: 0035-9254 ISO Abbreviation: J R Stat Soc Ser C Appl Stat Publication Date: 1981 |
Date Detail:
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Created Date: 1983-12-05 Completed Date: 1983-12-05 Revised Date: 2007-11-15 |
Medline Journal Info:
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Nlm Unique ID: 101086541 Medline TA: J R Stat Soc Ser C Appl Stat Country: England |
Other Details:
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Languages: eng Pagination: 286-95 Citation Subset: J |
Copyright Information:
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excerpt |
Export Citation:
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| MeSH Terms | |
Descriptor/Qualifier:
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Demography Developed Countries Europe Great Britain Mortality* Population Population Dynamics Regression Analysis* Research Statistics as Topic |
From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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