Melinda McCann
Statistics Department
Oklahoma State University
Simultaneous Inference for Prevalence Using Pooled Assessments
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, pooled testing has been used
in other applications as well, including drug testing, multiple-vector
transfer designs in plant pathology, and epidemiological studies involving
animal disease. Within a pooled-testing context, we consider situations
wherein different strata or treatments are to be compared with the goals of
assessing practical differences between strata and ranking strata in terms
of prevalence. To achieve these goals, we first derive two simultaneous
pairwise interval estimation procedures for use with pooled data. Our
procedures rely on asymptotic results, so we investigate small-sample
behaviour and compare the two procedures in terms of simultaneous coverage
probability and mean interval length. We then present a unified approach to
determining pool sizes which deliver desired coverage properties while
taking testing costs and interval precision into account. We illustrate our
methods using data from an observational hiv study involving heterosexual
males who use intravenous drugs.
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