Improved confidence intervals of a small probability from pooled testing with misclassification

Abstract

This article concerns construction of confidence intervals for the prevalence of a rare disease using Dorfman’s pooled testing procedure when the disease status is classified with an imperfect biomarker. Such an interval can be derived by converting a confidence interval for the probability that a group is tested positive. Wald confidence intervals based on a normal approximation are shown to be inefficient in terms of coverage probability, even for relatively large number of pools. A few alternatives are proposed and their performance is investigated in terms of coverage probability and length of intervals.