IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0334663.html
   My bibliography  Save this article

Evaluating the Cauchy combination test for count data

Author

Listed:
  • Huda Alsulami
  • Silvia Liverani

Abstract

The Cauchy combination test (CCT) is a p-value combination method used in multiple-hypothesis testing and is robust under dependence structures. This study aims to evaluate the CCT for independent and correlated count data where the individual p-values are derived from tests based on normal approximation to the negative binomial distribution. The correlated count data are modelled via copula methods. The CCT performance is evaluated in a simulation study to assess the type 1 error rate and the statistical power, and compare it with existing methods. Our results indicate that the number of combined tests, the negative binomial success parameter, and sample size significantly affect the type 1 error rate of the CCT under independence or moderate correlation. The CCT has more control over managing the type 1 error rate as the strength increases in the Gumbel-Hougaard copula. In general, the choice of copula and the strength of its correlation have a significant influence on type 1 error rates for both the CCT and MinP tests. Our simulation findings support the broader applications of the CCT under multivariate copulas that model upper-tail dependence with higher correlations. This knowledge may have significant implications for practical applications.

Suggested Citation

  • Huda Alsulami & Silvia Liverani, 2025. "Evaluating the Cauchy combination test for count data," PLOS ONE, Public Library of Science, vol. 20(10), pages 1-17, October.
    • Handle: RePEc:plo:pone00:0334663
    DOI: 10.1371/journal.pone.0334663
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0334663
    Download Restriction: no
    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0334663&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pone.0334663?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Gelio Alves & Yi-Kuo Yu, 2014. "Accuracy Evaluation of the Unified P-Value from Combining Correlated P-Values," PLOS ONE, Public Library of Science, vol. 9(3), pages 1-11, March.
    2. Kost, James T. & McDermott, Michael P., 2002. "Combining dependent P-values," Statistics & Probability Letters, Elsevier, vol. 60(2), pages 183-190, November.
    Full references (including those not matched with items on IDEAS)

    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. Xiaqiong Wang & Yalu Wen, 2020. "A Systematic Comparison of Methods Designed for Association Analysis with Multi-Omics Data," Biostatistics and Biometrics Open Access Journal, Juniper Publishers Inc., vol. 10(2), pages 30-40, August.
    2. Chien Li-Chu, 2020. "Combining dependent p-values by gamma distributions," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 19(4-6), pages 1-12, December.
    3. Arie Shaus & Yana Gerber & Shira Faigenbaum-Golovin & Barak Sober & Eli Piasetzky & Israel Finkelstein, 2020. "Forensic document examination and algorithmic handwriting analysis of Judahite biblical period inscriptions reveal significant literacy level," PLOS ONE, Public Library of Science, vol. 15(9), pages 1-15, September.
    4. Holm, Hakan J. & Samahita, Margaret, 2018. "Curating social image: Experimental evidence on the value of actions and selfies," Journal of Economic Behavior & Organization, Elsevier, vol. 148(C), pages 83-104.
    5. Oliver M. Crook & Colin T. R. Davies & Lisa M. Breckels & Josie A. Christopher & Laurent Gatto & Paul D. W. Kirk & Kathryn S. Lilley, 2022. "Inferring differential subcellular localisation in comparative spatial proteomics using BANDLE," Nature Communications, Nature, vol. 13(1), pages 1-21, December.
    6. Clara Bicalho & Adam Bouyamourn & Thad Dunning, 2022. "The Power of Prognosis: Improving Covariate Balance Tests with Outcome Information," Papers 2205.10478, arXiv.org, revised Oct 2025.
    7. Follmann, Dean & Proschan, Michael, 2012. "A test of location for exchangeable multivariate normal data with unknown correlation," Journal of Multivariate Analysis, Elsevier, vol. 104(1), pages 115-125, February.
    8. Sang Cheol Kim & Seul Ji Lee & Won Jun Lee & Young Na Yum & Joo Hwan Kim & Soojung Sohn & Jeong Hill Park & Jeongmi Lee & Johan Lim & Sung Won Kwon, 2013. "Stouffer’s Test in a Large Scale Simultaneous Hypothesis Testing," PLOS ONE, Public Library of Science, vol. 8(5), pages 1-11, May.
    9. Peter M. Aronow, 2012. "A General Method for Detecting Interference Between Units in Randomized Experiments," Sociological Methods & Research, , vol. 41(1), pages 3-16, February.

    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:plo:pone00:0334663. 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: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    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.