Year: 2018
Type: article
Abstract: Estimation using pooled sampling has long been an area of interest in the group testing literature. Such research has focused primarily on the assumed use of fixed sampling plans (i), although some recent papers have suggested alternative sequential designs that sample until a predetermined number of positive tests (ii). One major consideration, including in the new work on sequential plans, is the construction of debiased estimators that either reduce or keep the mean square error from inflating. However, whether under the above or other sampling designs unbiased estimation is in fact possible has yet to be established in the literature. In this article, we introduce a design that samples until a fixed number of negatives (iii), and show that an unbiased estimator exists under this model, whereas unbiased estimation is not possible for either of the preceding designs (i) and (ii). We present new estimators under the different sampling plans that are either unbiased or that have reduced bias relative to those already in use as well as generally improve on the mean square error. Numerical studies are done in order to compare designs in terms of bias and mean square error under practical situations with small and medium sample sizes.
Source: Sequential Analysis
Authors: Gregory Haber, Yaakov Malinovsky, Paul S. Albert
Language: English
Subfield: Statistics and Probability
Field: Mathematics
Domain: Physical Sciences
Open Access status: green
Funder: National Cancer Institute
OpenAlex ID: W2559571110