Two-Dimensional Informative Array Testing

Christopher S. McMahan, Joshua M. Tebbs, Christopher R. Bilder

Research output: Contribution to journalArticle

10 Citations (Scopus)

Abstract

Array-based group-testing algorithms for case identification are widely used in infectious disease testing, drug discovery, and genetics. In this article, we generalize previous statistical work in array testing to account for heterogeneity among individuals being tested. We first derive closed-form expressions for the expected number of tests (efficiency) and misclassification probabilities (sensitivity, specificity, predictive values) for two-dimensional array testing in a heterogeneous population. We then propose two "informative" array construction techniques which exploit population heterogeneity in ways that can substantially improve testing efficiency when compared to classical approaches that regard the population as homogeneous. Furthermore, a useful byproduct of our methodology is that misclassification probabilities can be estimated on a per-individual basis. We illustrate our new procedures using chlamydia and gonorrhea testing data collected in Nebraska as part of the Infertility Prevention Project.

Original languageEnglish (US)
Pages (from-to)793-804
Number of pages12
JournalBiometrics
Volume68
Issue number3
DOIs
StatePublished - Sep 1 2012

Fingerprint

Testing
Misclassification Probability
Chlamydia
Gonorrhea
Population Characteristics
Drug Discovery
Infertility
Population
Communicable Diseases
testing
Sensitivity and Specificity
Group Testing
Infectious Diseases
Specificity
Closed-form
Byproducts
byproducts
infectious diseases
Generalise
Methodology

Keywords

  • Disease screening
  • Efficiency
  • Group testing
  • Infertility Prevention Project
  • Matrix pooling
  • Pooled testing

ASJC Scopus subject areas

  • Statistics and Probability
  • Biochemistry, Genetics and Molecular Biology(all)
  • Immunology and Microbiology(all)
  • Agricultural and Biological Sciences(all)
  • Applied Mathematics

Cite this

Two-Dimensional Informative Array Testing. / McMahan, Christopher S.; Tebbs, Joshua M.; Bilder, Christopher R.

In: Biometrics, Vol. 68, No. 3, 01.09.2012, p. 793-804.

Research output: Contribution to journalArticle

McMahan, Christopher S. ; Tebbs, Joshua M. ; Bilder, Christopher R. / Two-Dimensional Informative Array Testing. In: Biometrics. 2012 ; Vol. 68, No. 3. pp. 793-804.
@article{21d7891189ce43489771b387a305af26,
title = "Two-Dimensional Informative Array Testing",
abstract = "Array-based group-testing algorithms for case identification are widely used in infectious disease testing, drug discovery, and genetics. In this article, we generalize previous statistical work in array testing to account for heterogeneity among individuals being tested. We first derive closed-form expressions for the expected number of tests (efficiency) and misclassification probabilities (sensitivity, specificity, predictive values) for two-dimensional array testing in a heterogeneous population. We then propose two {"}informative{"} array construction techniques which exploit population heterogeneity in ways that can substantially improve testing efficiency when compared to classical approaches that regard the population as homogeneous. Furthermore, a useful byproduct of our methodology is that misclassification probabilities can be estimated on a per-individual basis. We illustrate our new procedures using chlamydia and gonorrhea testing data collected in Nebraska as part of the Infertility Prevention Project.",
keywords = "Disease screening, Efficiency, Group testing, Infertility Prevention Project, Matrix pooling, Pooled testing",
author = "McMahan, {Christopher S.} and Tebbs, {Joshua M.} and Bilder, {Christopher R.}",
year = "2012",
month = "9",
day = "1",
doi = "10.1111/j.1541-0420.2011.01726.x",
language = "English (US)",
volume = "68",
pages = "793--804",
journal = "Biometrics",
issn = "0006-341X",
publisher = "Wiley-Blackwell",
number = "3",

}

TY - JOUR

T1 - Two-Dimensional Informative Array Testing

AU - McMahan, Christopher S.

AU - Tebbs, Joshua M.

AU - Bilder, Christopher R.

PY - 2012/9/1

Y1 - 2012/9/1

N2 - Array-based group-testing algorithms for case identification are widely used in infectious disease testing, drug discovery, and genetics. In this article, we generalize previous statistical work in array testing to account for heterogeneity among individuals being tested. We first derive closed-form expressions for the expected number of tests (efficiency) and misclassification probabilities (sensitivity, specificity, predictive values) for two-dimensional array testing in a heterogeneous population. We then propose two "informative" array construction techniques which exploit population heterogeneity in ways that can substantially improve testing efficiency when compared to classical approaches that regard the population as homogeneous. Furthermore, a useful byproduct of our methodology is that misclassification probabilities can be estimated on a per-individual basis. We illustrate our new procedures using chlamydia and gonorrhea testing data collected in Nebraska as part of the Infertility Prevention Project.

AB - Array-based group-testing algorithms for case identification are widely used in infectious disease testing, drug discovery, and genetics. In this article, we generalize previous statistical work in array testing to account for heterogeneity among individuals being tested. We first derive closed-form expressions for the expected number of tests (efficiency) and misclassification probabilities (sensitivity, specificity, predictive values) for two-dimensional array testing in a heterogeneous population. We then propose two "informative" array construction techniques which exploit population heterogeneity in ways that can substantially improve testing efficiency when compared to classical approaches that regard the population as homogeneous. Furthermore, a useful byproduct of our methodology is that misclassification probabilities can be estimated on a per-individual basis. We illustrate our new procedures using chlamydia and gonorrhea testing data collected in Nebraska as part of the Infertility Prevention Project.

KW - Disease screening

KW - Efficiency

KW - Group testing

KW - Infertility Prevention Project

KW - Matrix pooling

KW - Pooled testing

UR - http://www.scopus.com/inward/record.url?scp=84866773021&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84866773021&partnerID=8YFLogxK

U2 - 10.1111/j.1541-0420.2011.01726.x

DO - 10.1111/j.1541-0420.2011.01726.x

M3 - Article

C2 - 22212007

AN - SCOPUS:84866773021

VL - 68

SP - 793

EP - 804

JO - Biometrics

JF - Biometrics

SN - 0006-341X

IS - 3

ER -