Statistical Modelling 11 (2011), 115135
Transitional ideal point models for longitudinal multinomial outcomes
Mark de Rooij
Methodology and Statistics Group,
Psychological Institute,
Leiden University
B2300 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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