IDEAS home Printed from https://ideas.repec.org/p/boc/msug09/04.html
   My bibliography  Save this paper

Multilevel modeling of ordinal responses

Author

Listed:
  • Sophia Rabe-Hesketh

    (University of California–Berkeley)

Abstract

Ordered categorical responses can be analyzed with different kinds of logistic regression models, the most popular being the cumulative logit or proportional odds model. Alternatively, ordinal probit models can be specified. When the data have a nested structure, with repeated observations for the same individual (as in longitudinal or panel data), or students nested in schools, these models can be extended by including random effects. I will describe the models and show how they can be estimated using gllamm. I will mention some elaborations of the models such as nonproportional odds and heteroskedastic errors. Finally, I will discuss how to obtain different types of predicted probabilities for these models to assess model fit, to visualize the model graphically, and to make inferences for individual units.

Suggested Citation

  • Sophia Rabe-Hesketh, 2009. "Multilevel modeling of ordinal responses," Mexican Stata Users' Group Meetings 2009 04, Stata Users Group.
    • Handle: RePEc:boc:msug09:04
    as

    Download full text from publisher

    File URL: http://repec.org/msug2009/mex09sug_srh.zip
    File Function: presentation materials
    Download Restriction: no
    ---><---

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:boc:msug09:04. 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: Christopher F Baum (email available below). General contact details of provider: https://edirc.repec.org/data/stataea.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.