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Activity Number: 510 - Recent Development in Semiparametric and Nonparametric Methods
Type: Contributed
Date/Time: Wednesday, July 31, 2019 : 10:30 AM to 12:20 PM
Sponsor: International Chinese Statistical Association
Abstract #302931 Presentation
Title: Nonparametric Estimation of Distributions Based on Group Testing Results with Differential Misclassification
Author(s): Wei Zhang* and Aiyi Liu and Qizhai Li and Paul Albert
Companies: Eunice Kennedy Shriver National Institute of Child Health and Human Development, NIH and Eunice Kennedy Shriver National Institute of Child Health and Human Development, NIH and Academy of Mathematics and Systems Science, Chinese Academy of Science and National Cancer Insititute
Keywords: Coverage probability; Differential misclassification; Integrated absolute bias; Pooling; Prevalence; Rare disease

This article concerns the problem of estimating a continuous distribution in a diseased or nondiseased population when only group-based test results on the disease status are available from using a group testing strategy. The problem is challenging in that individual disease statuses are not observed and group testing results are often subject to misclassification, with further complication that the misclassification may be differential as the group size and the number of the diseased individuals in the group vary. We propose a method to construct nonparametric estimation of the distribution and obtain its asymptotic properties. The performance of the distribution estimator is evaluated under various design considerations concerning group sizes and classification errors. The method is exemplified with data from the National Health and Nutrition Examination Survey (NHANES) study to estimate the prevalence of chlamydia in urine samples and the distribution of blood monocyte percent in serum samples.

Authors who are presenting talks have a * after their name.

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