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Optimality of group testing in the presence of misclassification

Author

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  • Aiyi Liu
  • Chunling Liu
  • Zhiwei Zhang
  • Paul S. Albert

Abstract

Several optimality properties of Dorfman's (1943) group testing procedure are derived for estimation of the prevalence of a rare disease whose status is classified with error. Exact ranges of disease prevalence are obtained for which group testing provides more efficient estimation when group size increases. Copyright 2012, Oxford University Press.

Suggested Citation

  • Aiyi Liu & Chunling Liu & Zhiwei Zhang & Paul S. Albert, 2012. "Optimality of group testing in the presence of misclassification," Biometrika, Biometrika Trust, vol. 99(1), pages 245-251.
    • Handle: RePEc:oup:biomet:v:99:y:2012:i:1:p:245-251
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    File URL: http://hdl.handle.net/10.1093/biomet/asr064
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    Citations

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    Cited by:

    1. Xiong, Wenjun & Ding, Juan, 2015. "Robust procedures for experimental design in group testing considering misclassification," Statistics & Probability Letters, Elsevier, vol. 100(C), pages 35-41.
    2. Gregory Haber & Yaakov Malinovsky, 2020. "On the Construction of Unbiased Estimators for the Group Testing Problem," Sankhya A: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 82(1), pages 220-241, February.
    3. Lipnowski, Elliot & Ravid, Doron, 2021. "Pooled testing for quarantine decisions," Journal of Economic Theory, Elsevier, vol. 198(C).
    4. Md S. Warasi & Laura L. Hungerford & Kevin Lahmers, 2022. "Optimizing Pooled Testing for Estimating the Prevalence of Multiple Diseases," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 27(4), pages 713-727, December.
    5. Joshua M. Tebbs & Christopher S. McMahan & Christopher R. Bilder, 2013. "Two-Stage Hierarchical Group Testing for Multiple Infections with Application to the Infertility Prevention Project," Biometrics, The International Biometric Society, vol. 69(4), pages 1064-1073, December.
    6. Christopher S. McMahan & Joshua M. Tebbs & Timothy E. Hanson & Christopher R. Bilder, 2017. "Bayesian regression for group testing data," Biometrics, The International Biometric Society, vol. 73(4), pages 1443-1452, December.
    7. Xianzheng Huang & Md Shamim Sarker Warasi, 2017. "Maximum Likelihood Estimators in Regression Models for Error-prone Group Testing Data," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 44(4), pages 918-931, December.
    8. Nguyen, Ngoc T. & Bish, Ebru K. & Bish, Douglas R., 2021. "Optimal pooled testing design for prevalence estimation under resource constraints," Omega, Elsevier, vol. 105(C).
    9. Shih-Hao Huang & Mong-Na Lo Huang & Kerby Shedden & Weng Kee Wong, 2017. "Optimal group testing designs for estimating prevalence with uncertain testing errors," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 79(5), pages 1547-1563, November.
    10. Tarun Jain & Bijendra Nath Jain, 2021. "Infection Testing at Scale: An Examination of Pooled Testing Diagnostics," Vikalpa: The Journal for Decision Makers, , vol. 46(1), pages 13-26, March.
    11. Graham Hepworth & Brad J. Biggerstaff, 2021. "Bias Correction in Estimating Proportions by Imperfect Pooled Testing," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 26(1), pages 90-104, March.

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