IDEAS home Printed from https://ideas.repec.org/a/bla/biomet/v63y2007i4p1126-1134.html
   My bibliography  Save this article

Nonparametric Bayesian Estimation of Positive False Discovery Rates

Author

Listed:
  • Yongqiang Tang
  • Subhashis Ghosal
  • Anindya Roy

Abstract

No abstract is available for this item.

Suggested Citation

  • Yongqiang Tang & Subhashis Ghosal & Anindya Roy, 2007. "Nonparametric Bayesian Estimation of Positive False Discovery Rates," Biometrics, The International Biometric Society, vol. 63(4), pages 1126-1134, December.
  • Handle: RePEc:bla:biomet:v:63:y:2007:i:4:p:1126-1134
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1111/j.1541-0420.2007.00819.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. Allison, David B. & Gadbury, Gary L. & Heo, Moonseong & Fernandez, Jose R. & Lee, Cheol-Koo & Prolla, Tomas A. & Weindruch, Richard, 2002. "A mixture model approach for the analysis of microarray gene expression data," Computational Statistics & Data Analysis, Elsevier, vol. 39(1), pages 1-20, March.
    2. Chen-An Tsai & Huey-miin Hsueh & James J. Chen, 2003. "Estimation of False Discovery Rates in Multiple Testing: Application to Gene Microarray Data," Biometrics, The International Biometric Society, vol. 59(4), pages 1071-1081, December.
    3. Christopher Genovese & Larry Wasserman, 2002. "Operating characteristics and extensions of the false discovery rate procedure," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 64(3), pages 499-517, August.
    4. 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)

    Citations

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


    Cited by:

    1. Laurent Barras & Olivier Scaillet & Russ Wermers, 2010. "False Discoveries in Mutual Fund Performance: Measuring Luck in Estimated Alphas," Journal of Finance, American Finance Association, vol. 65(1), pages 179-216, February.
    2. Chang Yu & Daniel Zelterman, 2020. "Distributions associated with simultaneous multiple hypothesis testing," Journal of Statistical Distributions and Applications, Springer, vol. 7(1), pages 1-17, December.
    3. Federico Bassetti & Roberto Casarin & Francesco Ravazzolo, 2018. "Bayesian Nonparametric Calibration and Combination of Predictive Distributions," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 113(522), pages 675-685, April.
    4. Yu, Chang & Zelterman, Daniel, 2017. "A parametric model to estimate the proportion from true null using a distribution for p-values," Computational Statistics & Data Analysis, Elsevier, vol. 114(C), pages 105-118.

    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. Robert R. Delongchamp & John F. Bowyer & James J. Chen & Ralph L. Kodell, 2004. "Multiple-Testing Strategy for Analyzing cDNA Array Data on Gene Expression," Biometrics, The International Biometric Society, vol. 60(3), pages 774-782, September.
    2. Hunt, Daniel L. & Cheng, Cheng & Pounds, Stanley, 2009. "The beta-binomial distribution for estimating the number of false rejections in microarray gene expression studies," Computational Statistics & Data Analysis, Elsevier, vol. 53(5), pages 1688-1700, March.
    3. Ferreira, J.A. & Nyangoma, S.O., 2008. "A multivariate version of the Benjamini-Hochberg method," Journal of Multivariate Analysis, Elsevier, vol. 99(9), pages 2108-2124, October.
    4. A Bottle & P Aylin, 2011. "Predicting the false alarm rate in multi-institution mortality monitoring," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(9), pages 1711-1718, September.
    5. Ebrahimi, Nader, 2008. "Simultaneous control of false positives and false negatives in multiple hypotheses testing," Journal of Multivariate Analysis, Elsevier, vol. 99(3), pages 437-450, March.
    6. B. Moerkerke & E. Goetghebeur & J. De Riek & I. Roldán‐Ruiz, 2006. "Significance and impotence: towards a balanced view of the null and the alternative hypotheses in marker selection for plant breeding," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 169(1), pages 61-79, January.
    7. Qingyun Cai & Hock Peng Chan, 2017. "A Double Application of the Benjamini-Hochberg Procedure for Testing Batched Hypotheses," Methodology and Computing in Applied Probability, Springer, vol. 19(2), pages 429-443, June.
    8. 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.
    9. E. M. Conlon & B. L. Postier & B. A. Methe & K. P. Nevin & D. R. Lovley, 2009. "Hierarchical Bayesian meta-analysis models for cross-platform microarray studies," Journal of Applied Statistics, Taylor & Francis Journals, vol. 36(10), pages 1067-1085.
    10. Cheng, Cheng, 2009. "Internal validation inferences of significant genomic features in genome-wide screening," Computational Statistics & Data Analysis, Elsevier, vol. 53(3), pages 788-800, January.
    11. Izmirlian, Grant, 2020. "Strong consistency and asymptotic normality for quantities related to the Benjamini–Hochberg false discovery rate procedure," Statistics & Probability Letters, Elsevier, vol. 160(C).
    12. Xiang, Qinfang & Edwards, Jode & Gadbury, Gary L., 2006. "Interval estimation in a finite mixture model: Modeling P-values in multiple testing applications," Computational Statistics & Data Analysis, Elsevier, vol. 51(2), pages 570-586, November.
    13. Cipolli III, William & Hanson, Timothy & McLain, Alexander C., 2016. "Bayesian nonparametric multiple testing," Computational Statistics & Data Analysis, Elsevier, vol. 101(C), pages 64-79.
    14. Charnigo, Richard & Fan, Qian & Bittel, Douglas & Dai, Hongying, 2013. "Testing unilateral versus bilateral normal contamination," Statistics & Probability Letters, Elsevier, vol. 83(1), pages 163-167.
    15. 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.
    16. T. Tony Cai & Wenguang Sun, 2017. "Optimal screening and discovery of sparse signals with applications to multistage high throughput studies," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 79(1), pages 197-223, January.
    17. Shigeyuki Matsui & Shu Zeng & Takeharu Yamanaka & John Shaughnessy, 2008. "Sample Size Calculations Based on Ranking and Selection in Microarray Experiments," Biometrics, The International Biometric Society, vol. 64(1), pages 217-226, March.
    18. Simina M. Boca & Héctor Corrada Bravo & Brian Caffo & Jeffrey T. Leek & Giovanni Parmigiani, 2013. "A Decision‐Theory Approach to Interpretable Set Analysis for High‐Dimensional Data," Biometrics, The International Biometric Society, vol. 69(3), pages 614-623, September.
    19. Jiaying Gu & Roger Koenker, 2020. "Invidious Comparisons: Ranking and Selection as Compound Decisions," Papers 2012.12550, arXiv.org, revised Sep 2021.
    20. Debashis Ghosh & Wei Chen & Trivellore Raghuanthan, 2004. "The false discovery rate: a variable selection perspective," The University of Michigan Department of Biostatistics Working Paper Series 1040, Berkeley Electronic Press.

    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:63:y:2007:i:4:p:1126-1134. 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.