The efficient design of Nested Group Testing algorithms for disease identification in clustered data

DOI10.1080/02664763.2022.2071419OpenAlexW4229452925MaRDI QIDQ6164671

Ana F. Best, Yaakov Malinovsky, Paul S. Albert

Publication date: 28 July 2023

Published in: Journal of Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://figshare.com/articles/journal_contribution/The_efficient_design_of_Nested_Group_Testing_algorithms_for_disease_identification_in_clustered_data/19736441

zbMATH Keywords

clustered datagroup testingdisease identificationpooled sample analysisprevalence heterogeneity

Mathematics Subject Classification ID

Statistics (62-XX)

Cites Work

• Sterrett procedure for the generalized group testing problem
• Reader reaction: A note on the evaluation of group testing algorithms in the presence of misclassification
• Group Testing for Case Identification with Correlated Responses
• Confidence interval procedures for proportions estimated by group testing with groups of unequal size adjusted for overdispersion
• On the Detection of Defective Members of Large Populations
• A Generalized Binomial Group Testing Problem
• Group testing with a dilution effect
• An Optimum Nested Procedure in Binomial Group Testing
• The Exact Solution to the Two-Stage Group-Testing Problem
• Screening for the Presence of a Disease by Pooling Sera Samples
• Robustness of Group Testing in the Estimation of Proportions
• Nonparametric deconvolution of density estimation based on observed sums
• Pooled Testing for HIV Screening: Capturing the Dilution Effect
• Group Testing Regression Models with Fixed and Random Effects
• Revisiting Nested Group Testing Procedures: New Results, Comparisons, and Robustness

This page was built for publication: The efficient design of Nested Group Testing algorithms for disease identification in clustered data