IDEAS home Printed from https://ideas.repec.org/a/eee/matsoc/v23y1992i1p103-117.html
   My bibliography  Save this article

Are all linear paired comparison models empirically equivalent?

Author

Listed:
  • Stern, Hal

Abstract

No abstract is available for this item.

Suggested Citation

  • Stern, Hal, 1992. "Are all linear paired comparison models empirically equivalent?," Mathematical Social Sciences, Elsevier, vol. 23(1), pages 103-117, February.
    • Handle: RePEc:eee:matsoc:v:23:y:1992:i:1:p:103-117
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/0165-4896(92)90040-C
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

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


    Cited by:

    1. Karpov, Alexander, 2015. "A theory of knockout tournament seedings," Working Papers 0600, University of Heidelberg, Department of Economics.
    2. Baker, Rose D. & McHale, Ian G., 2014. "A dynamic paired comparisons model: Who is the greatest tennis player?," European Journal of Operational Research, Elsevier, vol. 236(2), pages 677-684.
    3. Mark Glickman, 2001. "Dynamic paired comparison models with stochastic variances," Journal of Applied Statistics, Taylor & Francis Journals, vol. 28(6), pages 673-689.
    4. Vincent Buskens & Jeroen Weesie, 2000. "An Experiment On The Effects Of Embeddedness In Trust Situations," Rationality and Society, , vol. 12(2), pages 227-253, May.
    5. Éva Orbán-Mihálykó & Csaba Mihálykó & László Koltay, 2019. "Incomplete paired comparisons in case of multiple choice and general log-concave probability density functions," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 27(2), pages 515-532, June.
    6. Vojnovic, Milan & Yun, Seyoung, 2016. "Parameter estimation for generalized thurstone choice models," LSE Research Online Documents on Economics 85703, London School of Economics and Political Science, LSE Library.
    7. Chan Victor, 2011. "Prediction Accuracy of Linear Models for Paired Comparisons in Sports," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 7(3), pages 1-35, July.

    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:eee:matsoc:v:23:y:1992:i:1:p:103-117. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/inca/505565 .

    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.