Meaningful regression and association models for clustered ordinal data
Jokinen, Jukka, McDonald, John W. and Smith, Peter W. F. (2006) Meaningful regression and association models for clustered ordinal data. Sociological Methodology (doi:10.1111/j.1467-9531.2006.00173.x).
Many proposed methods for analyzing clustered ordinal data focus on the regression model and consider the association structure within a cluster as a nuisance. However, often the association structure is of equal interest, for example, temporal association in longitudinal studies and association between responses to similar questions in a survey. We discuss the use, appropriateness and interpretability of various latent variable and Markov models for the association structure and propose a new structure that exploits the ordinality of the response. The models are illustrated with a study concerning opinions regarding government spending and an analysis of stability and change in teenage marijuana use over time, where we reveal different behavioral patterns for boys and girls through a comprehensive investigation of individual response profiles.
|Digital Object Identifier (DOI):||doi:10.1111/j.1467-9531.2006.00173.x|
|Subjects:||H Social Sciences > HA Statistics|
|Divisions:||University Structure - Pre August 2011 > Southampton Statistical Sciences Research Institute
|Date Deposited:||14 Jan 2005|
|Last Modified:||31 Mar 2016 11:26|
Modelling Attitude Stability and Change Using Repeated Measures Data
Funded by: ESRC (H333250026)
1 October 2003 to 30 April 2006
|RDF:||RDF+N-Triples, RDF+N3, RDF+XML, Browse.|
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