The article presents the results of an evaluation of a statistical method for estimating false positive and false negative reports from repeated measurement studies. The method was developed by Hui and Walter for evaluating medical diagnostic testing procedures. The article also presents a general model for studying misclassification in self-reported drug use and extends the model to the case where two measurements of the same characteristic are available for the sample of respondents. The article shows how the measures of reliability, measurement bias, estimator bias, mean squared error, false negative, and false positive probability can be defined in the context of the general model and how they may be estimated under the appropriate study designs. The article also demonstrates the use of Hui and Walter's method for evaluating the error in self-reported drug use. The article suggests that Hui and Walter's method should be considered for studies of drug use reporting error that use a biological test (hair, urine, or nail) to evaluate the error in the self-report. Tables, references