IDEAS home Printed from https://ideas.repec.org/a/oup/biomet/v105y2018i1p239-246..html
   My bibliography  Save this article

Choosing between methods of combining $p$-values

Author

Listed:
  • N A Heard
  • P Rubin-Delanchy

Abstract

Summary Combining $p$-values from independent statistical tests is a popular approach to meta-analysis, particularly when the data underlying the tests are either no longer available or are difficult to combine. Numerous $p$-value combination methods appear in the literature, each with different statistical properties, yet often the final choice used in a meta-analysis can seem arbitrary, as if all effort has been expended in building the models that gave rise to the $p$-values. Birnbaum (1954) showed that any reasonable $p$-value combiner must be optimal against some alternative hypothesis. Starting from this perspective and recasting each method of combining $p$-values as a likelihood ratio test, we present theoretical results for some standard combiners that provide guidance on how a powerful combiner might be chosen in practice.

Suggested Citation

  • N A Heard & P Rubin-Delanchy, 2018. "Choosing between methods of combining $p$-values," Biometrika, Biometrika Trust, vol. 105(1), pages 239-246.
  • Handle: RePEc:oup:biomet:v:105:y:2018:i:1:p:239-246.
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1093/biomet/asx076
    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.

    Citations

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


    Cited by:

    1. Xiong, Peihan & Hu, Taizhong, 2022. "On Samuel’s p-value model and the Simes test under dependence," Statistics & Probability Letters, Elsevier, vol. 187(C).
    2. Song, Zhi & Mukherjee, Amitava & Zhang, Jiujun, 2021. "Some robust approaches based on copula for monitoring bivariate processes and component-wise assessment," European Journal of Operational Research, Elsevier, vol. 289(1), pages 177-196.
    3. Leonhard Held, 2020. "The harmonic mean χ2‐test to substantiate scientific findings," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 69(3), pages 697-708, June.
    4. Paulo C. Rodrigues & Vanda M. Lourenço, 2020. "Comments on: Hierarchical Inference for genome-wide association studies: a view on methodology with software by Paulo C. Rodrigues and Vanda M. Lourenço," Computational Statistics, Springer, vol. 35(1), pages 57-58, March.
    5. Juan Antonio Villatoro-García & Jordi Martorell-Marugán & Daniel Toro-Domínguez & Yolanda Román-Montoya & Pedro Femia & Pedro Carmona-Sáez, 2022. "DExMA: An R Package for Performing Gene Expression Meta-Analysis with Missing Genes," Mathematics, MDPI, vol. 10(18), pages 1-15, September.
    6. Wimmer, Thomas & Geyer-Klingeberg, Jerome & Hütter, Marie & Schmid, Florian & Rathgeber, Andreas, 2021. "The impact of speculation on commodity prices: A Meta-Granger analysis," Journal of Commodity Markets, Elsevier, vol. 22(C).
    7. Jai Won Choi & Balgobin Nandram & Boseung Choi, 2022. "Combining Correlated P-values From Primary Data Analyses," International Journal of Statistics and Probability, Canadian Center of Science and Education, vol. 11(6), pages 1-12, November.
    8. Patrick B. Langthaler & Riccardo Ceccato & Luigi Salmaso & Rosa Arboretti & Arne C. Bathke, 2023. "Permutation testing for thick data when the number of variables is much greater than the sample size: recent developments and some recommendations," Computational Statistics, Springer, vol. 38(1), pages 101-132, March.
    9. Zimmermann, Paul, 2021. "The role of the leverage effect in the price discovery process of credit markets," Journal of Economic Dynamics and Control, Elsevier, vol. 122(C).

    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:oup:biomet:v:105:y:2018:i:1:p:239-246.. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Oxford University Press (email available below). General contact details of provider: https://academic.oup.com/biomet .

    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.