IDEAS home Printed from https://ideas.repec.org/a/bla/biomet/v74y2018i1p196-206.html
   My bibliography  Save this article

Fast approximation of small p†values in permutation tests by partitioning the permutations

Author

Listed:
  • Brian D. Segal
  • Thomas Braun
  • Michael R. Elliott
  • Hui Jiang

Abstract

Researchers in genetics and other life sciences commonly use permutation tests to evaluate differences between groups. Permutation tests have desirable properties, including exactness if data are exchangeable, and are applicable even when the distribution of the test statistic is analytically intractable. However, permutation tests can be computationally intensive. We propose both an asymptotic approximation and a resampling algorithm for quickly estimating small permutation p†values (e.g.,

Suggested Citation

  • Brian D. Segal & Thomas Braun & Michael R. Elliott & Hui Jiang, 2018. "Fast approximation of small p†values in permutation tests by partitioning the permutations," Biometrics, The International Biometric Society, vol. 74(1), pages 196-206, March.
  • Handle: RePEc:bla:biomet:v:74:y:2018:i:1:p:196-206
    DOI: 10.1111/biom.12731
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/biom.12731
    Download Restriction: no

    File URL: https://libkey.io/10.1111/biom.12731?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. Liang, Faming & Liu, Chuanhai & Carroll, Raymond J., 2007. "Stochastic Approximation in Monte Carlo Computation," Journal of the American Statistical Association, American Statistical Association, vol. 102, pages 305-320, March.
    2. Zhang, Yu & Liu, Jun S., 2011. "Fast and Accurate Approximation to Significance Tests in Genome-Wide Association Studies," Journal of the American Statistical Association, American Statistical Association, vol. 106(495), pages 846-857.
    3. Hui Jiang & Julia Salzman, 2012. "Statistical properties of an early stopping rule for resampling-based multiple testing," Biometrika, Biometrika Trust, vol. 99(4), pages 973-980.
    4. Janssen, Arnold, 1997. "Studentized permutation tests for non-i.i.d. hypotheses and the generalized Behrens-Fisher problem," Statistics & Probability Letters, Elsevier, vol. 36(1), pages 9-21, November.
    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. Shi Yang & Shi Weiping & Wang Mengqiao & Lee Ji-Hyun & Kang Huining & Jiang Hui, 2023. "Accurate and fast small p-value estimation for permutation tests in high-throughput genomic data analysis with the cross-entropy method," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 22(1), pages 1-22, January.

    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. Hagemann, Andreas, 2019. "Placebo inference on treatment effects when the number of clusters is small," Journal of Econometrics, Elsevier, vol. 213(1), pages 190-209.
    2. Jaehee Kim & Sooyoung Cheon, 2010. "A Bayesian regime‐switching time‐series model," Journal of Time Series Analysis, Wiley Blackwell, vol. 31(5), pages 365-378, September.
    3. Smaga, Łukasz, 2015. "Wald-type statistics using {2}-inverses for hypothesis testing in general factorial designs," Statistics & Probability Letters, Elsevier, vol. 107(C), pages 215-220.
    4. Axel Gandy & Georg Hahn, 2016. "A Framework for Monte Carlo based Multiple Testing," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 43(4), pages 1046-1063, December.
    5. Faming Liang & Momiao Xiong, 2013. "Bayesian Detection of Causal Rare Variants under Posterior Consistency," PLOS ONE, Public Library of Science, vol. 8(7), pages 1-16, July.
    6. Purevdorj Tuvaandorj, 2021. "Robust Permutation Tests in Linear Instrumental Variables Regression," Papers 2111.13774, arXiv.org, revised Jul 2024.
    7. Friedrich, Sarah & Brunner, Edgar & Pauly, Markus, 2017. "Permuting longitudinal data in spite of the dependencies," Journal of Multivariate Analysis, Elsevier, vol. 153(C), pages 255-265.
    8. Stefano Bonnini & Getnet Melak Assegie & Kamila Trzcinska, 2024. "Review about the Permutation Approach in Hypothesis Testing," Mathematics, MDPI, vol. 12(17), pages 1-29, August.
    9. Ian Barnett & Rajarshi Mukherjee & Xihong Lin, 2017. "The Generalized Higher Criticism for Testing SNP-Set Effects in Genetic Association Studies," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(517), pages 64-76, January.
    10. Chung, EunYi & Romano, Joseph P., 2016. "Multivariate and multiple permutation tests," Journal of Econometrics, Elsevier, vol. 193(1), pages 76-91.
    11. Federico A. Bugni & Ivan A. Canay & Azeem M. Shaikh, 2018. "Inference Under Covariate-Adaptive Randomization," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 113(524), pages 1784-1796, October.
    12. Chung, EunYi & Olivares, Mauricio, 2021. "Permutation test for heterogeneous treatment effects with a nuisance parameter," Journal of Econometrics, Elsevier, vol. 225(2), pages 148-174.
    13. Dennis Dobler & Markus Pauly, 2018. "Bootstrap- and permutation-based inference for the Mann–Whitney effect for right-censored and tied data," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 27(3), pages 639-658, September.
    14. Yuehao Bai & Joseph P. Romano & Azeem M. Shaikh, 2022. "Inference in Experiments With Matched Pairs," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 117(540), pages 1726-1737, October.
    15. Axel Gandy & Georg Hahn, 2014. "MMCTest—A Safe Algorithm for Implementing Multiple Monte Carlo Tests," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 41(4), pages 1083-1101, December.
    16. Cao, Jiajia & Zhou, Yanbin & Wei, Kun, 2024. "Modeling ants’ walks in patrolling multiple resources using stochastic approximation partial momentum refreshment," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 637(C).
    17. Juwon Seo, 2018. "Randomization Tests for Equality in Dependence Structure," Papers 1811.02105, arXiv.org.
    18. Steinke Ingo, 2004. "Locally asymptotically optimal tests in semiparametric generalized linear models in the 2-sample-problem," Statistics & Risk Modeling, De Gruyter, vol. 22(4), pages 319-334, April.
    19. Yukito Iba & Nen Saito & Akimasa Kitajima, 2014. "Multicanonical MCMC for sampling rare events: an illustrative review," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 66(3), pages 611-645, June.
    20. Young, Alwyn, 2024. "Asymptotically robust permutation-based randomization confidence intervals for parametric OLS regression," LSE Research Online Documents on Economics 120933, London School of Economics and Political Science, LSE Library.

    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:74:y:2018:i:1:p:196-206. 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.