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American Journal of Epidemiology Vol. 122, No. 3: 495-506
Copyright © 1985 by The Johns Hopkins University School of Hygiene and Public Health

research-article

CONFOUNDING AND MISCLASSIFICATION

SANDER GREENLAND1 3 and JAMES M. ROBINS2

1Division of Epidemiology, UCLA School of Public Health Los Angeles, CA 90024
2Occupational Health Program, Harvard School of Public Health Boston, MA

The authors examine some recently proposed criteria for determining when to adjust for covariates related to mlsdassification, and show these criteria to be incorrect In particular, they show that when misdassffication is present, covariate control can sometimes increase net bias, even when the covariate would have been a confounder under perfect classification, and even if the covariate is a determinant of classification. Thus, bias due to misclasstflcation cannot be adequately dealt with by the methods used for control of confounding. The examples presented also show that the "change-in-estimate" criterion for deciding whether to control a covariate can be systematically misleading when mis-classification is present These results demonstrate that it is necessary to consider the degree of misdassiflcation when deciding whether to control a covariate.

biometry; epidemiologic methods

3Partially supported by NCI grant RO-CA-16042


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