IDEAS home Printed from https://ideas.repec.org/a/bla/biomet/v69y2013i4p1064-1073.html
   My bibliography  Save this article

Two-Stage Hierarchical Group Testing for Multiple Infections with Application to the Infertility Prevention Project

Author

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

Abstract

No abstract is available for this item.

Suggested Citation

  • 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.
    • Handle: RePEc:bla:biomet:v:69:y:2013:i:4:p:1064-1073
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1111/biom.12080
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. 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.
    2. Delaigle, Aurore & Meister, Alexander, 2011. "Nonparametric Regression Analysis for Group Testing Data," Journal of the American Statistical Association, American Statistical Association, vol. 106(494), pages 640-650.
    3. 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.
    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

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    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. 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.
    3. Juan Ding & Wenjun Xiong, 2015. "Robust group testing for multiple traits with misclassification," Journal of Applied Statistics, Taylor & Francis Journals, vol. 42(10), pages 2115-2125, October.
    4. 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.
    5. Hrayer Aprahamian & Douglas R. Bish & Ebru K. Bish, 2019. "Optimal Risk-Based Group Testing," Management Science, INFORMS, vol. 65(9), pages 4365-4384, September.
    6. 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.
    7. 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.
    8. 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.
    9. 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).
    10. Yaakov Malinovsky & Paul S. Albert, 2015. "A Note on the Minimax Solution for the Two-Stage Group Testing Problem," The American Statistician, Taylor & Francis Journals, vol. 69(1), pages 45-52, February.
    11. 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.
    12. Wei Zhang & Aiyi Liu & Qizhai Li & Paul S. Albert, 2020. "Nonparametric estimation of distributions and diagnostic accuracy based on group‐tested results with differential misclassification," Biometrics, The International Biometric Society, vol. 76(4), pages 1147-1156, December.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. Gustavo Quinderé Saraiva, 2023. "Pool testing with dilution effects and heterogeneous priors," Health Care Management Science, Springer, vol. 26(4), pages 651-672, December.
    8. 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.
    9. 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.
    10. 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.
    11. 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.
    12. 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.
    13. 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.
    14. 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.
    15. Karl B. Gregory & Dewei Wang & Christopher S. McMahan, 2019. "Adaptive elastic net for group testing," Biometrics, The International Biometric Society, vol. 75(1), pages 13-23, March.
    16. 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.
    17. Xinlei Zuo & Juan Ding & Junjian Zhang & Wenjun Xiong, 2024. "Nonparametric Additive Regression for High-Dimensional Group Testing Data," Mathematics, MDPI, vol. 12(5), pages 1-21, February.
    18. Christopher S. McMahan & Joshua M. Tebbs & Christopher R. Bilder, 2012. "Two-Dimensional Informative Array Testing," Biometrics, The International Biometric Society, vol. 68(3), pages 793-804, September.
    19. Hrayer Aprahamian & Douglas R. Bish & Ebru K. Bish, 2019. "Optimal Risk-Based Group Testing," Management Science, INFORMS, vol. 65(9), pages 4365-4384, September.
    20. D. Wang & C. S. McMahan & C. M. Gallagher & K. B. Kulasekera, 2014. "Semiparametric group testing regression models," Biometrika, Biometrika Trust, vol. 101(3), pages 587-598.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bla:biomet:v:69:y:2013:i:4:p:1064-1073. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Wiley Content Delivery (email available below). General contact details of provider: http://www.blackwellpublishing.com/journal.asp?ref=0006-341X .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.