Statistical Modelling 11 (2011), 115–135

Transitional ideal point models for longitudinal multinomial outcomes

Mark de Rooij
Methodology and Statistics Group,
Psychological Institute,
Leiden University
B–2300 RB Leiden
The Netherlands
eMail: rooijm@fsw.leidenuniv.nl

Abstract:

For the analysis of longitudinal data, three families of models are generally distinguished: the marginal, the transitional and the subject-specific family. In this paper, we will propose a transitional model for the analysis of change for a nominal response variable. Such an analysis is often hampered by the dimensionality of the problem. We use multidimensional scaling techniques, more specifically the ideal point model, in order to reduce the dimensionality. The model can handle pure transitional data but also allows for explanatory variables. Two empirical examples will be discussed in order to illustrate all the virtues of the model.

Keywords:

biplots; categorical data; Markov models; multidimensional scaling

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