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

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 …

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 …

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 …

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

In the presentation and discussion of epidemiologic study results, investigators often argue
that their results have to be viewed as conservative due to the occurrence of presumedly …

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

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

Misclassification into exposure categories formed from a continuous variable arises from
measurement error in the continuous variable. Examples and mathematical results are …

This paper addresses potential effects of non-differential misclassification of polytomous
confounders on adjusted exposure-disease associations. Although the degree of …