Multilevel modeling of ordinal responses

Sophia Rabe-Hesketh

Mexican Stata Users' Group Meetings 2009 from Stata Users Group

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.

Date: 2009-06-05
New Economics Papers: this item is included in nep-dcm
References: Add references at CitEc
Citations:

Downloads: (external link)
http://repec.org/msug2009/mex09sug_srh.zip presentation materials (application/zip)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:boc:msug09:04

Access Statistics for this paper

More papers in Mexican Stata Users' Group Meetings 2009 from Stata Users Group Contact information at EDIRC.
Bibliographic data for series maintained by Christopher F Baum ().