When misclassification of exposure and disease is nondifferential but not independent of
one another, bias away from the null can result. For dichotomous variables, misclassification …

Background Many investigators write as if non-differential exposure misclassification
inevitably leads to a reduction in the strength of an estimated exposure–disease association …

The development of sophisticated methods for analysis of complex epidemiologic data is an
exciting area of methodologic research. However, investigators frequently face more basic …

Most of the literature on the effect of nondifferential misclassification and errors in variables
either addresses binary exposure variables or discusses continuous variables in the …

Researchers sometimes argue that their exposure-measurement errors are independent of
other errors and are nondifferential with respect to disease, resulting in estimation bias …

In case-control studies with three exposure levels where disease risk is associated with
exposure, the direction of bias in the odds ratios (ORs) from nondifferential misclassification …

This paper addresses the effects of simultaneous misclassification of both exposure and
disease on epidemiologic measures of association. If misclassification of a dichotomous …

Many epidemiologic investigations involve some discussion of exposure misclassification,
but rarely is there an attempt to adjust for misclassification formally in the statistical analysis …

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 …

Continuous exposure variables are frequently categorized in epidemiologic data analysis. It
has recently been shown that such categorization may transform nondifferential error in …