Journal Article

Design and Interpretation of Studies of Differential Exposure Measurement Error

Emily White

in American Journal of Epidemiology

Published on behalf of Johns Hopkins Bloomberg School of Public Health

Volume 157, issue 5, pages 380-387
Published in print March 2003 | ISSN: 0002-9262
Published online March 2003 | e-ISSN: 1476-6256 | DOI: http://dx.doi.org/10.1093/aje/kwf203
Design and Interpretation of Studies of Differential Exposure Measurement Error

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Differential exposure measurement error can have more adverse effects on estimates of exposure-disease associations than nondifferential measurement error, yet relatively little has been written about the design and interpretation of validity and reliability studies to assess differential measurement error. In this paper, a simple approximate equation is given for the effect of differential measurement error in a continuous exposure measure on the bias in the odds ratio. From this, it is shown that two parameters need to be estimated in validity/reliability studies in order to interpret the results in terms of the bias in the odds ratio in an epidemiologic study that will use the measure. The first is the correlation between the mismeasured and true exposure. The second is the differential bias (difference between cases and controls in the difference between mean measured and true exposure) relative to the true difference in exposure between cases and controls. It is shown that this latter parameter can be estimated in a method comparison study if one has a comparison measure that is unbiased or has nondifferential bias, so a perfect criterion measure is not needed. Researchers should consider measuring and reporting this parameter in validity/reliability studies when feasible.

Keywords: epidemiologic methods; measurement error; reliability; validity; Abbreviations: OR, odds ratio; FFQ, food frequency questionnaire.

Journal Article.  5498 words.  Illustrated.

Subjects: Public Health and Epidemiology

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