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Initially announced by Dorfman in 1943, (Binomial) Group Testing (BGT) was quickly recognized as a useful tool in many other fields as well. To apply any particular BGT procedure effectively, one first of all needs to know an important…

Methodology · Statistics 2023-04-17 Ugnė Čižikovienė , Viktor Skorniakov

Randomization is a common technique used in clinical trials to eliminate potential bias and confounders in a patient population. Equal allocation to treatment groups is the standard due to its optimal efficiency in many cases. However, in…

Applications · Statistics 2020-04-09 Thevaa Chandereng , Xiaodan Wei , Rick Chappell

Randomization tests are a popular method for testing causal effects in clinical trials with finite-sample validity. In the presence of heterogeneous treatment effects, it is often of interest to select a subgroup that benefits from the…

Methodology · Statistics 2025-04-29 Zijun Gao

It is frequently of interest to jointly analyze two paired sequences of multiple tests. This paper studies the problem of detecting whether there are more pairs of tests that are significant in both sequences than would be expected by…

Methodology · Statistics 2017-06-26 Sihai Dave Zhao , T. Tony Cai , Hongzhe Li

Group testing was conceived during World War II to identify soldiers infected with syphilis using as few tests as possible, and it has attracted renewed interest during the COVID-19 pandemic. A long-standing assumption in the probabilistic…

Social and Information Networks · Computer Science 2022-11-18 Surin Ahn , Wei-Ning Chen , Ayfer Ozgur

Recent papers initiated the study of a generalization of group testing where the potentially contaminated sets are the members of a given hypergraph F=(V,E). This generalization finds application in contexts where contaminations can be…

Data Structures and Algorithms · Computer Science 2024-07-02 Annalisa De Bonis

Quick and accurate medical diagnosis is crucial for the successful treatment of a disease. Using machine learning algorithms, we have built two models to predict a hematologic disease, based on laboratory blood test results. In one…

Machine Learning · Statistics 2020-06-09 Gregor Gunčar , Matjaž Kukar , Mateja Notar , Miran Brvar , Peter Černelč , Manca Notar , Marko Notar

In this paper, we consider the problem of designing optimal pooling matrix for group testing (for example, for COVID-19 virus testing) with the constraint that no more than $r>0$ samples can be pooled together, which we call "dilution…

Quantitative Methods · Quantitative Biology 2020-08-06 Jirong Yi , Myung Cho , Xiaodong Wu , Raghu Mudumbai , Weiyu Xu

In this paper, we propose a computer-oriented method of construction of optimal group sequential hypothesis tests with variable group sizes. In particular, for independent and identically distributed observations we obtain the form of…

Methodology · Statistics 2023-03-30 Andrey Novikov

The global testing problem studied in this paper is to seek a definite answer to whether a system of concurrent black-boxes has an observable behavior in a given finite (but could be huge) set "Bad". We introduce a novel approach to solve…

Software Engineering · Computer Science 2007-05-23 Gaoyan Xie , Zhe Dang

The basic goal of threshold group testing is to identify up to $d$ defective items among a population of $n$ items, where $d$ is usually much smaller than $n$. The outcome of a test on a subset of items is positive if the subset has at…

Information Theory · Computer Science 2021-08-24 Thach V. Bui , Mahdi Cheraghchi , Isao Echizen

In probabilistic nonadaptive group testing (PGT), we aim to characterize the number of pooled tests necessary to identify a random $k$-sparse vector of defectives with high probability. Recent work has shown that $n$ tests are necessary…

Information Theory · Computer Science 2021-06-15 Larkin Flodin , Arya Mazumdar

Group testing can help maintain a widespread testing program using fewer resources amid a pandemic. In group testing, we are given $n$ samples, one per individual. These samples are arranged into $m < n$ pooled samples, where each pool is…

Information Theory · Computer Science 2022-01-20 Ritesh Goenka , Shu-Jie Cao , Chau-Wai Wong , Ajit Rajwade , Dror Baron

We study Dorfman's classical group testing protocol in a novel setting where individual specimen statuses are modeled as exchangeable random variables. We are motivated by infectious disease screening. In that case, specimens which arrive…

Applications · Statistics 2024-02-28 Nicholas C. Landolfi , Sanjay Lall

Threshold tests have recently been proposed as a useful method for detecting bias in lending, hiring, and policing decisions. For example, in the case of credit extensions, these tests aim to estimate the bar for granting loans to white and…

Machine Learning · Statistics 2018-03-13 Emma Pierson , Sam Corbett-Davies , Sharad Goel

Debiased estimation has long been an area of research in the group testing literature. This has led to the development of several estimators with the goal of bias minimization and, recently, an unbiased estimator based on sequential…

Methodology · Statistics 2018-06-08 Gregory Haber , Yaakov Malinovsky

Computer-based tests with randomly generated questions allow a large number of different tests to be generated. Given a fixed number of alternatives for each question, the number of tests that need to be generated before all possible…

Probability · Mathematics 2010-03-04 Charles M. Goldie , Rosie Cornish , Carol L. Robinson

Genome-wide association analysis has generated much discussion about how to preserve power to detect signals despite the detrimental effect of multiple testing on power. We develop a weighted multiple testing procedure that facilitates the…

Statistics Theory · Mathematics 2007-06-13 Kathryn Roeder , Bernie Devlin , Larry Wasserman

It is the efficient use of resources expected from an exam scheduling application. There are various criteria for efficient use of resources and for all tests to be carried out at minimum cost in the shortest possible time. It is aimed that…

Artificial Intelligence · Computer Science 2019-02-05 Murat Dener , M. Hanefi Calp

The group testing problem is concerned with identifying a small set of $k$ infected individuals in a large population of $n$ people. At our disposal is a testing scheme that can test groups of individuals. A test comes back positive if and…

Information Theory · Computer Science 2021-03-25 Oliver Gebhard , Philipp Loick