Three-Dimensional Array-Based Group Testing Algorithms

We derive the operating characteristics of three-dimensional array-based testing algorithms for case identification in the presence of testing error. The operating characteristics investigated include efficiency (i.e., expected number of tests per specimen) and error rates (e.g., sensitivity, specif...

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Published inBiometrics Vol. 65; no. 3; pp. 903 - 910
Main Authors Kim, Hae-Young, Hudgens, Michael G
Format Journal Article
LanguageEnglish
Published Malden, USA Blackwell Publishing Inc 01.09.2009
Wiley-Blackwell
Blackwell Publishing Ltd
Subjects
Online AccessGet full text
ISSN0006-341X
1541-0420
1541-0420
DOI10.1111/j.1541-0420.2008.01158.x

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Abstract We derive the operating characteristics of three-dimensional array-based testing algorithms for case identification in the presence of testing error. The operating characteristics investigated include efficiency (i.e., expected number of tests per specimen) and error rates (e.g., sensitivity, specificity, positive, and negative predictive values). The methods are illustrated by comparing the proposed algorithms with previously studied hierarchical and two-dimensional array algorithms for detecting recent HIV infections in North Carolina. Our results indicate that three-dimensional array-based algorithms can be more efficient and accurate than previously proposed algorithms in settings with test error and low prevalence.
AbstractList We derive the operating characteristics of three-dimensional array-based testing algorithms for case identification in the presence of testing error. The operating characteristics investigated include efficiency (i.e., expected number of tests per specimen) and error rates (e.g., sensitivity, specificity, positive, and negative predictive values). The methods are illustrated by comparing the proposed algorithms with previously studied hierarchical and two-dimensional array algorithms for detecting recent HIV infections in North Carolina. Our results indicate that three-dimensional array-based algorithms can be more efficient and accurate than previously proposed algorithms in settings with test error and low prevalence.
Summary We derive the operating characteristics of three‐dimensional array‐based testing algorithms for case identification in the presence of testing error. The operating characteristics investigated include efficiency (i.e., expected number of tests per specimen) and error rates (e.g., sensitivity, specificity, positive, and negative predictive values). The methods are illustrated by comparing the proposed algorithms with previously studied hierarchical and two‐dimensional array algorithms for detecting recent HIV infections in North Carolina. Our results indicate that three‐dimensional array‐based algorithms can be more efficient and accurate than previously proposed algorithms in settings with test error and low prevalence.
Summary We derive the operating characteristics of three‐dimensional array‐based testing algorithms for case identification in the presence of testing error. The operating characteristics investigated include efficiency (i.e., expected number of tests per specimen) and error rates (e.g., sensitivity, specificity, positive, and negative predictive values). The methods are illustrated by comparing the proposed algorithms with previously studied hierarchical and two‐dimensional array algorithms for detecting recent HIV infections in North Carolina. Our results indicate that three‐dimensional array‐based algorithms can be more efficient and accurate than previously proposed algorithms in settings with test error and low prevalence.
We derive the operating characteristics of three-dimensional array-based testing algorithms for case identification in the presence of testing error. The operating characteristics investigated include efficiency (i.e., expected number of tests per specimen) and error rates (e.g., sensitivity, specificity, positive, and negative predictive values). The methods are illustrated by comparing the proposed algorithms with previously studied hierarchical and two-dimensional array algorithms for detecting recent HIV infections in North Carolina. Our results indicate that three-dimensional array-based algorithms can be more efficient and accurate than previously proposed algorithms in settings with test error and low prevalence. [PUBLICATION ABSTRACT]
We derive the operating characteristics of three-dimensional array-based testing algorithms for case identification in the presence of testing error. The operating characteristics investigated include efficiency (i.e., expected number of tests per specimen) and error rates (e.g., sensitivity, specificity, positive, and negative predictive values). The methods are illustrated by comparing the proposed algorithms with previously studied hierarchical and two-dimensional array algorithms for detecting recent HIV infections in North Carolina. Our results indicate that three-dimensional array-based algorithms can be more efficient and accurate than previously proposed algorithms in settings with test error and low prevalence.We derive the operating characteristics of three-dimensional array-based testing algorithms for case identification in the presence of testing error. The operating characteristics investigated include efficiency (i.e., expected number of tests per specimen) and error rates (e.g., sensitivity, specificity, positive, and negative predictive values). The methods are illustrated by comparing the proposed algorithms with previously studied hierarchical and two-dimensional array algorithms for detecting recent HIV infections in North Carolina. Our results indicate that three-dimensional array-based algorithms can be more efficient and accurate than previously proposed algorithms in settings with test error and low prevalence.
Author Hudgens, Michael G.
Kim, Hae-Young
AuthorAffiliation 1 Center for Statistical Analysis and Research, New England Research Institutes, 9 Galen Street, Watertown, Massachusetts 02472, U.S.A
2 Department of Biostatistics, School of Public Health, University of North Carolina at Chapel Hill, 3107-E McGavran-Greenberg Hall, Chapel Hill, North Carolina 27599, U.S.A
AuthorAffiliation_xml – name: 1 Center for Statistical Analysis and Research, New England Research Institutes, 9 Galen Street, Watertown, Massachusetts 02472, U.S.A
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Snippet We derive the operating characteristics of three-dimensional array-based testing algorithms for case identification in the presence of testing error. The...
Summary We derive the operating characteristics of three‐dimensional array‐based testing algorithms for case identification in the presence of testing error....
Summary We derive the operating characteristics of three‐dimensional array‐based testing algorithms for case identification in the presence of testing error....
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StartPage 903
SubjectTerms AIDS
Algorithms
Alternatives
Array
Biometric Methodology
Biometrics
biometry
Biometry - methods
Biostatistics
Cost efficiency
Data Interpretation, Statistical
Diagnosis, Computer-Assisted - methods
Efficiency
Error analysis
Error rates
Group testing
Hierarchical
HIV
HIV infections
Humans
Mass Screening - methods
North Carolina
Nucleic acids
Population Dynamics
Population Surveillance - methods
Predictive value
Sensitivity
Specificity
Specimens
Working papers
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Title Three-Dimensional Array-Based Group Testing Algorithms
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