Robust analysis of clustered binary data: beta-binomial model under response misclassification

Abstract

New estimators and predictors for the beta-binomial model that are robust to binary data misclassifications are proposed. It is proved that the proposed estimators are consistent and the proposed predictors have the minimum mean square error in the case of known distortion levels. The efficiency of the methods is illustrated on real data from mediaplanning.