IDEAS home Printed from https://ideas.repec.org/a/inm/ormksc/v5y1986i4p325-344.html
   My bibliography  Save this article

A Probabilistic Model for the Multidimensional Scaling of Proximity and Preference Data

Author

Listed:
  • David B. MacKay

    (Indiana University)

  • Joseph L. Zinnes

    (University of Illinois, Urbana)

Abstract

A probabilistic multidimensional scaling model that estimates both location and variance parameters for proximity and preference data is described and compared to a deterministic scaling model. Simulated and empirical choice data are used to compare models. Variance estimates from the probabilistic model are used to test a hypothesis about the homogeneity of stimulus perception under alternative modes of stimulus presentation.

Suggested Citation

  • David B. MacKay & Joseph L. Zinnes, 1986. "A Probabilistic Model for the Multidimensional Scaling of Proximity and Preference Data," Marketing Science, INFORMS, vol. 5(4), pages 325-344.
    • Handle: RePEc:inm:ormksc:v:5:y:1986:i:4:p:325-344
    DOI: 10.1287/mksc.5.4.325
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/mksc.5.4.325
    Download Restriction: no
    File URL: https://libkey.io/10.1287/mksc.5.4.325?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. Abe, Makoto, 1998. "Error structure and identification condition in maximum likelihood nonmetric multidimensional scaling," European Journal of Operational Research, Elsevier, vol. 111(2), pages 216-227, December.
    2. Dawn Iacobucci & Doug Grisaffe & Wayne DeSarbo, 2017. "Statistical perceptual maps: using confidence region ellipses to enhance the interpretations of brand positions in multidimensional scaling," Journal of Marketing Analytics, Palgrave Macmillan, vol. 5(3), pages 81-98, December.
    3. van de Velden, M. & de Beuckelaer, A. & Groenen, P.J.F. & Busing, F.M.T.A., 2011. "Nonmetric Unfolding of Marketing Data: Degeneracy and Stability," ERIM Report Series Research in Management ERS-2011-006-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    4. Bowen, William M., 1995. "A Thurstonian comparison of the analytic hierarchy process and probabilistic multidimensional scaling through application to the nuclear waste site selection decision," Socio-Economic Planning Sciences, Elsevier, vol. 29(2), pages 151-163, June.
    5. Elrod, Terry & Keane, Michael, 1995. "A Factor-Analytic Probit Model for Representing the Market Structure in Panel Data," MPRA Paper 52434, University Library of Munich, Germany.
    6. Gower, J.C. & Groenen, P.J.F. & van de Velden, M. & Vines, K., 2010. "Perceptual maps: the good, the bad and the ugly," ERIM Report Series Research in Management ERS-2010-011-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.

    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:inm:ormksc:v:5:y:1986:i:4:p:325-344. 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: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .

    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.