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Aiyi Liu - National Institutes of Health

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Optimality of Group Testing in the Presence of Misclassification
29 September 2011 from 4:00 PM to 5:00 PM
111 Tyson Building
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Aimed at more efficient screening of a rare disease, Dorfman (1943) proposed to test for syphilis antigen by first testing pooled blood samples, followed by retesting of individuals in groups found to be infected. This strategy and its variations developed later, often referred to as group testing or pooled testing, have received substantial attention for efficient identification of an event or estimation of the probability that the event occurs.


In this paper we further investigate the optimality properties of group testing strategy in estimating the prevalence of a disease.  We show that, when the disease status is measured with error, group testing with moderate group sizes provides more efficient estimation than the fully observed data over a wide range of disease prevalence. When the number of groups is fixed, group testing also prevails over the one-subject-per-group random sampling design for moderate disease prevalence. We discuss applications to evaluation of gene-environment interactions, and proposed a strata-based group testing strategy for such an evaluation.

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