ML Estimation from Binomial Data with Misclassifications

Summary

Tenenbein (1970) presented a double sampling scheme to estimate the proportion parameter of binomial data in presence of misclassification. In the context of measurement error models this strategy is known as the internal validation method. A second broad strategy is the use of repeated measurements. We show how to apply this strategy for the estimation of a binomial proportion parameter and try to answer the question which method should be preferred by comparing the asymptotic variances of the estimators.