IDEAS home Printed from https://ideas.repec.org/a/eee/stapro/v168y2021ics0167715220302467.html
   My bibliography  Save this article

Bound on FWER for correlated normal

Author

Listed:
  • Das, Nabaneet
  • Bhandari, Subir Kumar

Abstract

We have considered equicorrelated observations from normal distribution for simultaneous testing problem. In this article, we have shown that FWER asymptotically is a convex function of the correlation (ρ) and hence an upper bound on the FWER of Bonferroni-α procedure is α(1−ρ). This implies that Bonferroni’s method actually controls the FWER at a much smaller level than the desired level of significance under the positively correlated case and necessitates a correlation correction.

Suggested Citation

  • Das, Nabaneet & Bhandari, Subir Kumar, 2021. "Bound on FWER for correlated normal," Statistics & Probability Letters, Elsevier, vol. 168(C).
    • Handle: RePEc:eee:stapro:v:168:y:2021:i:c:s0167715220302467
    DOI: 10.1016/j.spl.2020.108943
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0167715220302467
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.spl.2020.108943?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
    ---><---

    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. Efron, Bradley, 2010. "Correlated z-Values and the Accuracy of Large-Scale Statistical Estimates," Journal of the American Statistical Association, American Statistical Association, vol. 105(491), pages 1042-1055.
    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. Dey, Monitirtha & Bhandari, Subir Kumar, 2023. "FWER goes to zero for correlated normal," Statistics & Probability Letters, Elsevier, vol. 193(C).

    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. 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.
    2. de Uña-Alvarez Jacobo, 2011. "On the Statistical Properties of SGoF Multitesting Method," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 10(1), pages 1-30, April.
    3. Tiago C. Silva & Juan I. Young & Lanyu Zhang & Lissette Gomez & Michael A. Schmidt & Achintya Varma & X. Steven Chen & Eden R. Martin & Lily Wang, 2022. "Cross-tissue analysis of blood and brain epigenome-wide association studies in Alzheimer’s disease," Nature Communications, Nature, vol. 13(1), pages 1-16, December.
    4. 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.
    5. Bickel David R., 2012. "Empirical Bayes Interval Estimates that are Conditionally Equal to Unadjusted Confidence Intervals or to Default Prior Credibility Intervals," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 11(3), pages 1-34, February.
    6. Sairam Rayaprolu & Zhiyi Chi, 2021. "False Discovery Variance Reduction in Large Scale Simultaneous Hypothesis Tests," Methodology and Computing in Applied Probability, Springer, vol. 23(3), pages 711-733, September.
    7. Jianqing Fan & Yuan Liao & Martina Mincheva, 2013. "Large covariance estimation by thresholding principal orthogonal complements," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 75(4), pages 603-680, September.
    8. de Uña-Alvarez Jacobo, 2012. "The Beta-Binomial SGoF method for multiple dependent tests," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 11(3), pages 1-32, May.
    9. Bickel David R., 2013. "Simple estimators of false discovery rates given as few as one or two p-values without strong parametric assumptions," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 12(4), pages 529-543, August.
    10. Jules L. Ellis & Klaas Sijtsma, 2023. "A Test to Distinguish Monotone Homogeneity from Monotone Multifactor Models," Psychometrika, Springer;The Psychometric Society, vol. 88(2), pages 387-412, June.
    11. Jianqing Fan & Quefeng Li & Yuyan Wang, 2017. "Estimation of high dimensional mean regression in the absence of symmetry and light tail assumptions," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 79(1), pages 247-265, January.
    12. Peilin Jia & Lily Wang & Ayman H Fanous & Carlos N Pato & Todd L Edwards & The International Schizophrenia Consortium & Zhongming Zhao, 2012. "Network-Assisted Investigation of Combined Causal Signals from Genome-Wide Association Studies in Schizophrenia," PLOS Computational Biology, Public Library of Science, vol. 8(7), pages 1-11, July.
    13. Pei Fen Kuan & Derek Y. Chiang, 2012. "Integrating Prior Knowledge in Multiple Testing under Dependence with Applications to Detecting Differential DNA Methylation," Biometrics, The International Biometric Society, vol. 68(3), pages 774-783, September.
    14. Anat Reiner-Benaim, 2016. "Scan Statistic Tail Probability Assessment Based on Process Covariance and Window Size," Methodology and Computing in Applied Probability, Springer, vol. 18(3), pages 717-745, September.
    15. Dey, Monitirtha & Bhandari, Subir Kumar, 2023. "FWER goes to zero for correlated normal," Statistics & Probability Letters, Elsevier, vol. 193(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:eee:stapro:v:168:y:2021:i:c:s0167715220302467. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/622892/description#description .

    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.