Sequential estimation in the group testing problem

TL;DR

This paper introduces a new sequential sampling design in group testing that allows for unbiased estimation and improves mean square error, addressing limitations of previous fixed and other sequential plans.

Contribution

It proposes a novel sampling plan sampling until a fixed number of negatives and demonstrates unbiased estimation is possible under this design, unlike others.

Findings

Unbiased estimator exists for the new negative-based sampling plan.

The new estimators reduce bias and improve mean square error.

Numerical studies show improved performance in small and medium samples.

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 which either reduce or keep the mean square error from inflating. Whether, however, under the above or other sampling designs unbiased estimation is in fact possible has yet to be established in the literature. In this paper, we introduce a design which samples until a fixed number of negatives (iii), and show that an unbiased estimator exists under this model, while 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.