English  |  正體中文  |  简体中文  |  Post-Print筆數 : 27 |  Items with full text/Total items : 109952/140891 (78%)
Visitors : 46233886      Online Users : 998
RC Version 6.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
Scope Tips:
  • please add "double quotation mark" for query phrases to get precise results
  • please goto advance search for comprehansive author search
    •  Adv. Search
    Home ‧ Login ‧ Upload ‧ Help ‧ About ‧ Administer Goto mobile version
    政大機構典藏 > 商學院 > 統計學系 > 期刊論文 >  Item 140.119/18152


    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/18152


    Title: Estimation of False Discovery Rates in Multiple Testing: Application to Gene Microarray Data
    Authors: Hsueh,Huey-miin;Tsai,Chen-An;Chen J. J.
    薛慧敏;蔡政安
    Keywords: Bayesian Type I error;Comparison-wise error rate (CWE);False discovery rate (FDR);Number of rejections;Number of true null hypotheses;q-value
    Date: 2003-12
    Issue Date: 2008-12-19 14:51:16 (UTC+8)
    Abstract: Testing for significance with gene expression data from DNA microarray experiments involves simultaneous comparisons of hundreds or thousands of genes. If R denotes the number of rejections (declared significant genes) and V denotes the number of false rejections, then V/R, if R > 0, is the proportion of false rejected hypotheses. This paper proposes a model for the distribution of the number of rejections and the conditional distribution of V given R, V | R. Under the independence assumption, the distribution of R is a convolution of two binomials and the distribution of V | R has a noncentral hypergeometric distribution. Under an equicorrelated model, the distributions are more complex and are also derived. Five false discovery rate probability error measures are considered: FDR = E(V/R), pFDR = E(V/R | R > 0) (positive FDR), cFDR = E(V/R | R = r) (conditional FDR), mFDR = E(V)/E(R) (marginal FDR), and eFDR = E(V)/r (empirical FDR). The pFDR, cFDR, and mFDR are shown to be equivalent under the Bayesian framework, in which the number of true null hypotheses is modeled as a random variable. We present a parametric and a bootstrap procedure to estimate the FDRs. Monte Carlo simulations were conducted to evaluate the performance of these two methods. The bootstrap procedure appears to perform reasonably well, even when the alternative hypotheses are correlated (ρ = .25). An example from a toxicogenomic microarray experiment is presented for illustration.
    Relation: Biometrics, 59(4),1073-1083
    Data Type: article
    DOI 連結: http://dx.doi.org/10.1111/j.0006-341X.2003.00123.x
    DOI: 10.1111/j.0006-341X.2003.00123.x
    Appears in Collections:[統計學系] 期刊論文

    Files in This Item:

    File Description SizeFormat
    1071-1081.pdf189KbAdobe PDF2806View/Open


    All items in 政大典藏 are protected by copyright, with all rights reserved.


    社群 sharing

    著作權政策宣告 Copyright Announcement
    1.本網站之數位內容為國立政治大學所收錄之機構典藏，無償提供學術研究與公眾教育等公益性使用，惟仍請適度，合理使用本網站之內容，以尊重著作權人之權益。商業上之利用，則請先取得著作權人之授權。
    The digital content of this website is part of National Chengchi University Institutional Repository. It provides free access to academic research and public education for non-commercial use. Please utilize it in a proper and reasonable manner and respect the rights of copyright owners. For commercial use, please obtain authorization from the copyright owner in advance.

    2.本網站之製作，已盡力防止侵害著作權人之權益，如仍發現本網站之數位內容有侵害著作權人權益情事者，請權利人通知本網站維護人員(nccur@nccu.edu.tw)，維護人員將立即採取移除該數位著作等補救措施。
    NCCU Institutional Repository is made to protect the interests of copyright owners. If you believe that any material on the website infringes copyright, please contact our staff(nccur@nccu.edu.tw). We will remove the work from the repository and investigate your claim.
    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - Feedback