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IJE Advance Access originally published online on January 9, 2008
International Journal of Epidemiology 2008 37(2):382-385; doi:10.1093/ije/dym291
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Published by Oxford University Press on behalf of the International Epidemiological Association © The Author 2008; all rights reserved.

Brief Report

How far from non-differential does exposure or disease misclassification have to be to bias measures of association away from the null?

Anne M Jurek1,*, Sander Greenland2 and George Maldonado3

1 Department of Pediatrics, University of Minnesota, Minneapolis, MN, USA.
2 Department of Epidemiology and Department of Statistics, University of California, Los Angeles, CA, USA.
3 Division of Environmental Health Sciences, University of Minnesota, Minneapolis, MN, USA.

* Corresponding author. Department of Pediatrics, University of Minnesota, Mayo Mail Code 715, 420 Delaware St. SE, Minneapolis, MN 55455, USA. E-mail: jure0007{at}umn.edu


   Abstract

A well-known heuristic in epidemiology is that non-differential exposure or disease misclassification biases the expected values of an estimator toward the null value. This heuristic works correctly only when additional conditions are met, such as independence of classification errors. We present examples to show that, even when the additional conditions are met, if the misclassification is only approximately non-differential, then bias is not guaranteed to be toward the null. In light of such examples, we advise that evaluation of misclassification should not be based on the assumption of exact non-differentiality unless the latter can be deduced logically from the facts of the situation.


Keywords Exposure measurement, misclassification, odds ratio, prevalence, sensitivity analysis

Accepted 17 December 2007


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