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Design Concepts in Nutritional Epidemiology$
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Barrie M. Margetts and Michael Nelson

Print publication date: 1997

Print ISBN-13: 9780192627391

Published to Oxford Scholarship Online: September 2009

DOI: 10.1093/acprof:oso/9780192627391.001.0001

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4. Covariate measurement errors in nutritional epidemiology: effects and remedies

4. Covariate measurement errors in nutritional epidemiology: effects and remedies

Chapter:
(p.87) 4. Covariate measurement errors in nutritional epidemiology: effects and remedies
Source:
Design Concepts in Nutritional Epidemiology
Author(s):

David Clayton

Caroline Gill

Publisher:
Oxford University Press
DOI:10.1093/acprof:oso/9780192627391.003.0004

The key problem in epidemiological studies is the identification of relevant exposures and outcomes, and the relationship (and error modelling) between observed and relevant measures, and between relevant measures and relevant outcomes. Measurement errors and bias undermine the ability to detect diet-disease relationships, and the problem is particularly acute in nutritional epidemiological studies because of the difficulties of measuring relevant dietary exposures accurately, and the particular problem of differential misclassification (i.e., the differences in bias in the measurements between individuals, or between one subset of a sample and another). Correcting for measurement error is a controversial topic, but the chapter provides illustrations of the extent of attenuation or misrepresentation of diet-disease associations.

Keywords:   relevant exposure, true exposure, measurement error, bias, differential misclassification, attenuation, validity, reproducibility, statistical techniques

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