IDEAS home Printed from https://ideas.repec.org/a/bla/jorssb/v67y2005i2p269-283.html
   My bibliography  Save this article

Model determination for categorical data with factor level merging

Author

Listed:
  • Petros Dellaportas
  • Claudia Tarantola

Abstract

Summary. We deal with contingency table data that are used to examine the relationships between a set of categorical variables or factors. We assume that such relationships can be adequately described by the cond`itional independence structure that is imposed by an undirected graphical model. If the contingency table is large, a desirable simplified interpretation can be achieved by combining some categories, or levels, of the factors. We introduce conditions under which such an operation does not alter the Markov properties of the graph. Implementation of these conditions leads to Bayesian model uncertainty procedures based on reversible jump Markov chain Monte Carlo methods. The methodology is illustrated on a 2×3×4 and up to a 4×5×5×2×2 contingency table.

Suggested Citation

  • Petros Dellaportas & Claudia Tarantola, 2005. "Model determination for categorical data with factor level merging," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 67(2), pages 269-283, April.
  • Handle: RePEc:bla:jorssb:v:67:y:2005:i:2:p:269-283
    DOI: 10.1111/j.1467-9868.2005.00501.x
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/j.1467-9868.2005.00501.x
    Download Restriction: no

    File URL: https://libkey.io/10.1111/j.1467-9868.2005.00501.x?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. Webb, Emily L. & Forster, Jonathan J., 2008. "Bayesian model determination for multivariate ordinal and binary data," Computational Statistics & Data Analysis, Elsevier, vol. 52(5), pages 2632-2649, January.
    2. Consonni, Guido & Massam, Hélène, 2012. "Parametrizations and reference priors for multinomial decomposable graphical models," Journal of Multivariate Analysis, Elsevier, vol. 105(1), pages 380-396.

    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:jorssb:v:67:y:2005:i:2:p:269-283. 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: Wiley Content Delivery (email available below). General contact details of provider: https://edirc.repec.org/data/rssssea.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.