title: Differential misclassification arising from nondifferential errors in exposure measurement.
abstract: Misclassification into exposure categories formed from a continuous variable arises from measurement error in the continuous variable. Examples and mathematical results are presented to show that if the measurement error is nondifferential (independent of disease status), the resulting misclassification will often be differential, even in cohort studies. The degree and direction of differential misclassification vary with the exposure distribution, the category definitions, the measurement error distribution, and the exposure-disease relation. Failure to recognize the likelihood of differential misclassification may lead to incorrect conclusions about the effects of measurement error on estimates of relative risk when categories are formed from continuous variables, such as dietary intake. Simulations were used to examine some effects of nondifferential measurement error. Under the conditions used, nondifferential measurement error reduced relative risk estimates, but not to the degree predicted by the assumption of nondifferential misclassification. When relative risk estimates were corrected using methods appropriate for nondifferential misclassification, the "corrected" relative risks were almost always higher than the true relative risks, sometimes considerably higher. The greater the measurement error, the more inaccurate was the correction. The effects of exposure measurement errors need more critical evaluation.
authors.affiliation: Division of Health Examination Statistics, Centers for Disease Control, Hyattsville, MD.
authors.forename: K M
authors.initials: KM
authors.lastname: Flegal
authors.forename: P M
authors.initials: PM
authors.lastname: Keyl
authors.forename: F J
authors.initials: FJ
authors.lastname: Nieto
mesh_terms: D015982:Bias; D015984:Causality; D015331:Cohort Studies; D004194:Disease / Q000145:classification* / Q000209:etiology; D004812:Epidemiologic Methods; D006801:Humans; D015233:Models, Statistical; D015995:Prevalence; D012680:Sensitivity and Specificity