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Improved Confidence Intervals of a Small Probability from Pooled Testing with Misclassification

机译:错误分类的合并测试可提高小概率的置信区间

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摘要

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.
机译:本文涉及在疾病状态用不完善的生物标记物分类时,使用多夫曼(Dorfman)的合并测试程序来构建罕见疾病患病率的置信区间。这样的间隔可以通过将置信区间转换为一个组被测试为阳性的概率来得出。即使对于相对大量的池,基于正态近似的Wald置信区间在覆盖概率方面也显示出低效。提出了一些替代方案,并根据覆盖概率和间隔长度来研究其性能。

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