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Bayesian Analysis and Design for Joint Modeling of Two Binary Responses With Misclassification

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Sociological Methods & Research

Published online on

Abstract

Survey data are often subject to various types of errors such as misclassification. In this article, we consider a model where interest is simultaneously in two correlated response variables and one is potentially subject to misclassification. A motivating example of a recent study of the impact of a sexual education course for adolescents is considered. A simulation-based sample size determination scheme is applied to illustrate the impact of misclassification on power and bias for the parameters of interest.