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Estimating the Prevalence of a Disease, Subject to Misclassification

Assume that we investigate the existence of a particular disease in a population to estimate the ratio of subjects that share it, but for misclassifying the subjects, we have some misclassification errors. We may distinguish a subject haying the disease that donʹt have that disease, and vice versa. In this article, we consider the problem of estimating the prevalence of a disease, under misclassification errors. We study the maximum likelihood estimator, the adjusted maximum likelihood estimator, the confidence interval of the prevalence, as well as the problem of sample size, subject to misclassification.