In epidemiologic studies, individuals may be misclassified with respect to exposure to a risk factor for disease. Such misclassification causes the relative risk of disease associated with the exposure in the population to be biased toward the null value. Here, a formula is derived for the apparent relative risk under misclassification (R) as a function of the sensitivity (U) and specificity (V) of the test for exposure and of the true relative risk (R) and true prevalence of exposure (P(E] in the population. The relative influence of U and V on the bias in R depends both on R and on P(E), with U tending to be more influential at higher values of P(E). When there is misclassification of exposure, variation in P(E) may bias comparisons of relative risk between groups or exposures, either by producing spurious differences or by masking true differences, and may generate spurious trends associated with a third variable such as age. Because the possible effects of misclassification of exposure on relative risk are complex and not easily generalized, the potential degree of bias should be evaluated individually in each situation.