Joshua Tebbs
Department of Statistics
Kansas State University
Pooled Testing with Covariates
When estimating the prevalence of a rare trait such as human
immunodeficiency virus (HIV), the use of pooled testing can confer
substantial benefits when compared to individual testing. In addition to
screening experiments for infectious diseases in humans, pooled testing has
also been exploited in other biomedical applications such as drug discovery,
epidemiological studies in animal populations, plant-disease assessment, and
screening for rare genetic mutations. Pooled testing is not a new idea, but,
until recently, nearly all biomedical studies using pooled testing have
treated individuals as homogeneous. In most real problems, researchers have
access to covariate information on each individual subject, and a major
thrust is geared towards (a) integrating this information into the analysis
appropriately, and (b) understanding how this information influences the
estimates. In this talk, I will give an overview of some of the
contributions that I have made to the pooled-testing estimation problem in
the presence of covariates. I will illustrate these contributions with real
data and will conclude by discussing some of my proposed research currently
in review at the National Institutes of Health.
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