One widely used measure of familial aggregation is the sibling recurrence-risk ratio, which is defined as the ratio of risk of disease manifestation, given that one's sibling is affected, as compared with the disease prevalence in the general population. Known as lambdaS, it has been used extensively in the mapping of complex diseases. In this paper, I show that, for a fictitious disease that is strictly nongenetic and nonenvironmental, lambdaS can be dramatically inflated because of misunderstanding of the original definition of lambdaS, ascertainment bias, and overreporting. Therefore, for a disease of entirely environmental origin, the lambdaS inflation due to ascertainment bias and/or overreporting is expected to be more prominent if the risk factor also is familially aggregated. This suggests that, like segregation analysis, the estimation of lambdaS also is prone to ascertainment bias and should be performed with great care. This is particularly important if one uses lambdaS for exclusion mapping, for discrimination between different genetic models, and for association studies, since these practices hinge tightly on an accurate estimation of lambdaS.