Ecological associations of fat intake with breast cancer incidence have not, in general, been corroborated by individual-based epidemiological studies. Profound mismeasurement, which, in these studies, probably typifies measures of dietary exposures in general and of fat in particular may, in part, explain this lack of agreement. To demonstrate the way in which error masks effects, we studied the impact of extreme mismeasurement in analysis of strong or moderate underlying associations using computer-simulated, case-control studies (300 cases, 300 controls). Severe error causes the mean and median odds ratios to be biased toward unity, tests for trend and upper category odds ratios to be often not significant, and lower category odds ratios frequently to exceed higher exposure ones. Important risk relationships can be concealed, despite careful design and analysis if there is substantial mismeasurement of exposure.