Revisiting Nested Group Testing Procedures: New Results, Comparisons, and Robustness

Date

2018-06-04

Department

Program

Citation of Original Publication

Malinovsky, Yaakov, and Paul S. Albert. “Revisiting Nested Group Testing Procedures: New Results, Comparisons, and Robustness.” The American Statistician 73, no. 2 (April 3, 2019): 117–25. https://doi.org/10.1080/00031305.2017.1366367.

Rights

This work was written as part of one of the author's official duties as an Employee of the United States Government and is therefore a work of the United States Government. In accordance with 17 U.S.C. 105, no copyright protection is available for such works under U.S. Law.
Public Domain

Abstract

Group testing has its origin in the identification of syphilis in the U.S. army during World War II. Much of the theoretical framework of group testing was developed starting in the late 1950s, with continued work into the 1990s. Recently, with the advent of new laboratory and genetic technologies, there has been an increasing interest in group testing designs for cost saving purposes. In this article, we compare different nested designs, including Dorfman, Sterrett and an optimal nested procedure obtained through dynamic programming. To elucidate these comparisons, we develop closed-form expressions for the optimal Sterrett procedure and provide a concise review of the prior literature for other commonly used procedures. We consider designs where the prevalence of disease is known as well as investigate the robustness of these procedures, when it is incorrectly assumed. This article provides a technical presentation that will be of interest to researchers as well as from a pedagogical perspective. Supplementary material for this article is available online.