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Informative Dorfman Screening

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

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  • Christopher S. McMahan & Joshua M. Tebbs & Christopher R. Bilder, 2012. "Informative Dorfman Screening," Biometrics, The International Biometric Society, vol. 68(1), pages 287-296, March.
    • Handle: RePEc:bla:biomet:v:68:y:2012:i:1:p:287-296
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    File URL: http://hdl.handle.net/10.1111/j.1541-0420.2011.01644.x
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    References listed on IDEAS

    as
    1. Xie M. & Tatsuoka K. & Sacks J. & Young S.S., 2001. "Group Testing With Blockers and Synergism," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 92-102, March.
    2. S. Vansteelandt & E. Goetghebeur & T. Verstraeten, 2000. "Regression Models for Disease Prevalence with Diagnostic Tests on Pools of Serum Samples," Biometrics, The International Biometric Society, vol. 56(4), pages 1126-1133, December.
    3. Hae-Young Kim & Michael G. Hudgens, 2009. "Three-Dimensional Array-Based Group Testing Algorithms," Biometrics, The International Biometric Society, vol. 65(3), pages 903-910, September.
    4. Hae-Young Kim & Michael G. Hudgens & Jonathan M. Dreyfuss & Daniel J. Westreich & Christopher D. Pilcher, 2007. "Comparison of Group Testing Algorithms for Case Identification in the Presence of Test Error," Biometrics, The International Biometric Society, vol. 63(4), pages 1152-1163, December.
    5. Bilder, Christopher R. & Tebbs, Joshua M. & Chen, Peng, 2010. "Informative Retesting," Journal of the American Statistical Association, American Statistical Association, vol. 105(491), pages 942-955.
    Full references (including those not matched with items on IDEAS)

    Citations

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    Cited by:

    1. 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.
    2. Hrayer Aprahamian & Douglas R. Bish & Ebru K. Bish, 2019. "Optimal Risk-Based Group Testing," Management Science, INFORMS, vol. 65(9), pages 4365-4384, September.
    3. Hrayer Aprahamian & Hadi El-Amine, 2022. "Optimal Screening of Populations with Heterogeneous Risk Profiles Under the Availability of Multiple Tests," INFORMS Journal on Computing, INFORMS, vol. 34(1), pages 150-164, January.
    4. 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.
    5. Hussein El Hajj & Douglas R. Bish & Ebru K. Bish & Denise M. Kay, 2022. "Novel Pooling Strategies for Genetic Testing, with Application to Newborn Screening," Management Science, INFORMS, vol. 68(11), pages 7994-8014, November.
    6. 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.
    7. Pritha Guha, 2022. "Application of Pooled Testing Methodologies in Tackling the COVID-19 Pandemic," Management and Labour Studies, XLRI Jamshedpur, School of Business Management & Human Resources, vol. 47(1), pages 7-21, February.
    8. 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.
    9. David Hong & Rounak Dey & Xihong Lin & Brian Cleary & Edgar Dobriban, 2022. "Group testing via hypergraph factorization applied to COVID-19," Nature Communications, Nature, vol. 13(1), pages 1-13, December.
    10. Wang, Dewei & McMahan, Christopher S. & Tebbs, Joshua M. & Bilder, Christopher R., 2018. "Group testing case identification with biomarker information," Computational Statistics & Data Analysis, Elsevier, vol. 122(C), pages 156-166.
    11. Gustavo Quinderé Saraiva, 2023. "Pool testing with dilution effects and heterogeneous priors," Health Care Management Science, Springer, vol. 26(4), pages 651-672, December.
    12. Hrayer Aprahamian & Douglas R. Bish & Ebru K. Bish, 2020. "Optimal Group Testing: Structural Properties and Robust Solutions, with Application to Public Health Screening," INFORMS Journal on Computing, INFORMS, vol. 32(4), pages 895-911, October.
    13. Chase N. Joyner & Christopher S. McMahan & Joshua M. Tebbs & Christopher R. Bilder, 2020. "From mixed effects modeling to spike and slab variable selection: A Bayesian regression model for group testing data," Biometrics, The International Biometric Society, vol. 76(3), pages 913-923, September.
    14. Christopher R. Bilder & Joshua M. Tebbs & Christopher S. McMahan, 2019. "Informative group testing for multiplex assays," Biometrics, The International Biometric Society, vol. 75(1), pages 278-288, March.
    15. 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.

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