IDEAS home Printed from https://ideas.repec.org/a/bla/biomet/v69y2013i1p1-7.html
   My bibliography  Save this article

Estimation of False Discovery Rate Using Sequential Permutation p-Values

Author

Listed:
  • Tim Bancroft
  • Chuanlong Du
  • Dan Nettleton

Abstract

No abstract is available for this item.

Suggested Citation

  • Tim Bancroft & Chuanlong Du & Dan Nettleton, 2013. "Estimation of False Discovery Rate Using Sequential Permutation p-Values," Biometrics, The International Biometric Society, vol. 69(1), pages 1-7, March.
  • Handle: RePEc:bla:biomet:v:69:y:2013:i:1:p:1-7
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1111/j.1541-0420.2012.01825.x
    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. David Ruppert & Dan Nettleton & J. T. Gene Hwang, 2007. "Exploring the Information in p-Values for the Analysis and Planning of Multiple-Test Experiments," Biometrics, The International Biometric Society, vol. 63(2), pages 483-495, June.
    2. Yoav Benjamini & Yosef Hochberg, 2000. "On the Adaptive Control of the False Discovery Rate in Multiple Testing With Independent Statistics," Journal of Educational and Behavioral Statistics, , vol. 25(1), pages 60-83, March.
    3. Kun Liang & Dan Nettleton, 2012. "Adaptive and dynamic adaptive procedures for false discovery rate control and estimation," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 74(1), pages 163-182, January.
    4. John D. Storey & Jonathan E. Taylor & David Siegmund, 2004. "Strong control, conservative point estimation and simultaneous conservative consistency of false discovery rates: a unified approach," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 66(1), pages 187-205, February.
    5. Dan Nettleton & R. W. Doerge, 2000. "Accounting for Variability in the Use of Permutation Testing to Detect Quantitative Trait Loci," Biometrics, The International Biometric Society, vol. 56(1), pages 52-58, March.
    6. Mette Langaas & Bo Henry Lindqvist & Egil Ferkingstad, 2005. "Estimating the proportion of true null hypotheses, with application to DNA microarray data," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 67(4), pages 555-572, September.
    7. John D. Storey, 2002. "A direct approach to false discovery rates," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 64(3), pages 479-498, August.
    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. Shigeyuki Matsui & Hisashi Noma, 2011. "Estimating Effect Sizes of Differentially Expressed Genes for Power and Sample-Size Assessments in Microarray Experiments," Biometrics, The International Biometric Society, vol. 67(4), pages 1225-1235, December.
    2. Kong Xin-Bing & Xu Qin-Feng, 2015. "On False Discovery and Non-discovery Proportions of the Dynamic Adaptive Procedure," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 42(2), pages 530-544, June.
    3. Sermpinis, Georgios & Hassanniakalager, Arman & Stasinakis, Charalampos & Psaradellis, Ioannis, 2021. "Technical analysis profitability and Persistence: A discrete false discovery approach on MSCI indices," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 73(C).
    4. Ferreira José A. & Berkhof Johannes & Souverein Olga & Zwinderman Koos, 2009. "A Multiple Testing Approach to High-Dimensional Association Studies with an Application to the Detection of Associations between Risk Factors of Heart Disease and Genetic Polymorphisms," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 8(1), pages 1-56, January.
    5. Long Qu & Dan Nettleton & Jack C. M. Dekkers, 2012. "Improved Estimation of the Noncentrality Parameter Distribution from a Large Number of t-Statistics, with Applications to False Discovery Rate Estimation in Microarray Data Analysis," Biometrics, The International Biometric Society, vol. 68(4), pages 1178-1187, December.
    6. Chen, Xiongzhi, 2019. "Uniformly consistently estimating the proportion of false null hypotheses via Lebesgue–Stieltjes integral equations," Journal of Multivariate Analysis, Elsevier, vol. 173(C), pages 724-744.
    7. Georgios Sermpinis & Arman Hassanniakalager & Charalampos Stasinakis & Ioannis Psaradellis, 2018. "Technical Analysis and Discrete False Discovery Rate: Evidence from MSCI Indices," Papers 1811.06766, arXiv.org, revised Jun 2019.
    8. Guo Wenge & Peddada Shyamal, 2008. "Adaptive Choice of the Number of Bootstrap Samples in Large Scale Multiple Testing," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 7(1), pages 1-21, March.
    9. Zehetmayer Sonja & Graf Alexandra C. & Posch Martin, 2015. "Sample size reassessment for a two-stage design controlling the false discovery rate," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 14(5), pages 429-442, November.
    10. Habiger, Joshua D. & Adekpedjou, Akim, 2014. "Optimal rejection curves for exact false discovery rate control," Statistics & Probability Letters, Elsevier, vol. 94(C), pages 21-28.
    11. Yoav Benjamini, 2010. "Discovering the false discovery rate," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 72(4), pages 405-416, September.
    12. Kim, Donggyu & Zhang, Chunming, 2014. "Adaptive linear step-up multiple testing procedure with the bias-reduced estimator," Statistics & Probability Letters, Elsevier, vol. 87(C), pages 31-39.
    13. Cai, Qingyun, 2018. "A scoring criterion for rejection of clustered p-values," Computational Statistics & Data Analysis, Elsevier, vol. 121(C), pages 180-189.
    14. Rohit Kumar Patra & Bodhisattva Sen, 2016. "Estimation of a two-component mixture model with applications to multiple testing," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 78(4), pages 869-893, September.
    15. Helmut Finner & Veronika Gontscharuk, 2009. "Controlling the familywise error rate with plug‐in estimator for the proportion of true null hypotheses," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 71(5), pages 1031-1048, November.
    16. David Ruppert & Dan Nettleton & J. T. Gene Hwang, 2007. "Exploring the Information in p-Values for the Analysis and Planning of Multiple-Test Experiments," Biometrics, The International Biometric Society, vol. 63(2), pages 483-495, June.
    17. Bajgrowicz, Pierre & Scaillet, Olivier, 2012. "Technical trading revisited: False discoveries, persistence tests, and transaction costs," Journal of Financial Economics, Elsevier, vol. 106(3), pages 473-491.
    18. Jianqing Fan & Xu Han, 2017. "Estimation of the false discovery proportion with unknown dependence," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 79(4), pages 1143-1164, September.
    19. Van Hanh Nguyen & Catherine Matias, 2014. "On Efficient Estimators of the Proportion of True Null Hypotheses in a Multiple Testing Setup," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 41(4), pages 1167-1194, December.
    20. Lianming Wang & David B. Dunson, 2010. "Semiparametric Bayes Multiple Testing: Applications to Tumor Data," Biometrics, The International Biometric Society, vol. 66(2), pages 493-501, June.

    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:1:p:1-7. 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.