IDEAS home Printed from https://ideas.repec.org/a/sae/jedbes/v25y2000i2p101-132.html
   My bibliography  Save this article

A Critique and Improvement of the CL Common Language Effect Size Statistics of McGraw and Wong

Author

Listed:
  • András Vargha
  • Harold D. Delaney

Abstract

McGraw and Wong (1992) described an appealing index of effect size, called CL, which measures the difference between two populations in terms of the probability that a score sampled at random from the first population will be greater than a score sampled at random from the second. McGraw and Wong introduced this "common language effect size statistic" for normal distributions and then proposed an approximate estimation for any continuous distribution. In addition, they generalized CL to the n-group case, the correlated samples case, and the discrete values case . In the current paper a different generalization of CL, called the A measure of stochastic superiority, is proposed, which may be directly applied for any discrete or continuous variable that is at least ordinally scaled. Exact methods for point and interval estimation as well as the significance tests of the A = .5 hypothesis are provided. New generalizations of CL are provided for the multi-group and correlated samples cases.

Suggested Citation

  • András Vargha & Harold D. Delaney, 2000. "A Critique and Improvement of the CL Common Language Effect Size Statistics of McGraw and Wong," Journal of Educational and Behavioral Statistics, , vol. 25(2), pages 101-132, June.
    • Handle: RePEc:sae:jedbes:v:25:y:2000:i:2:p:101-132
    DOI: 10.3102/10769986025002101
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.3102/10769986025002101
    Download Restriction: no
    File URL: https://libkey.io/10.3102/10769986025002101?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
    ---><---

    Citations

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


    Cited by:

    1. David R. Mandel & Christopher W. Karvetski & Mandeep K. Dhami, 2018. "Boosting intelligence analysts’ judgment accuracy: What works, what fails?," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 13(6), pages 607-621, November.
    2. repec:cup:judgdm:v:13:y:2018:i:6:p:607-621 is not listed on IDEAS
    3. Matthew B. Welsh & Steve H. Begg, 2018. "More-or-less elicitation (MOLE): reducing bias in range estimation and forecasting," EURO Journal on Decision Processes, Springer;EURO - The Association of European Operational Research Societies, vol. 6(1), pages 171-212, June.
    4. Chen, Lixin, 2017. "Do patent citations indicate knowledge linkage? The evidence from text similarities between patents and their citations," Journal of Informetrics, Elsevier, vol. 11(1), pages 63-79.
    5. Alexander Schacht & Kris Bogaerts & Erich Bluhmki & Emmanuel Lesaffre, 2008. "A New Nonparametric Approach for Baseline Covariate Adjustment for Two-Group Comparative Studies," Biometrics, The International Biometric Society, vol. 64(4), pages 1110-1116, December.

    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:sae:jedbes:v:25:y:2000:i:2:p:101-132. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: SAGE Publications (email available below). General contact details of provider: .

    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.