PoolTestR: An R package for estimating prevalence and regression modelling with pooled samples.
@article{McLure2020PoolTestRAR, title={PoolTestR: An R package for estimating prevalence and regression modelling with pooled samples.}, author={Angus McLure and Ben O'Neill and Helen J. Mayfield and Colleen L. Lau and Brady McPherson}, journal={arXiv: Computation}, year={2020} }
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References
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A frequentist Bernoulli-Beta hierarchical model is presented to relax the constant prevalence assumption underlying the traditional prevalence estimation approach based on pooled data, which is called into question when sampling from a large geographic area.
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It is shown that, under most conditions in which one would want to use group testing, most of the error results from sampling and not the pooling process, and the meaning of confidence intervals associated with prevalence estimates and the appropriate interpretation of these intervals are discussed.
Confidence intervals for proportions estimated by group testing with groups of unequal size
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Group testing, in which units are pooled together and tested as a group for the presence of an attribute, has been used in many fields of study, including blood testing, plant disease assessment,…
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It is concluded that variable pool size coupled with MLE is critical for accurate estimates of mosquito infection rates in WNV epidemic seasons.
Pooled Testing for Expanding COVID-19 Mass Surveillance
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Pool testing is shown to be able to detect positive samples with sufficient accuracy and can easily be used with existing equipment and personnel for population-wide screening.
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