Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/87109 
Year of Publication: 
2006
Series/Report no.: 
Quaderni di Dipartimento - EPMQ No. 187
Publisher: 
Università degli Studi di Pavia, Dipartimento di Economia Politica e Metodi Quantitativi (EPMQ), Pavia
Abstract: 
We deal with two-way contingency tables having ordered column categories. We use a row effects model wherein each interaction term is assumed to have a multiplicative form involving a row effect parameter and a fixed column score. We propose a methodology to cluster row effects in order to simplify the interaction structure and enhancing the interpretation of the model. Our method uses a product partition model with a suitable specification of the cohesion function, so that we can carry out our analysis on a collection of models of varying dimensions using a straightforward MCMC sampler. The methodology is illustrated with reference to simulated and real data sets.
Subjects: 
Clustering
Contingency table
Log-linear model
Markov Chain Monte Carlo
Mixture of Dirichlet process prior
Partition
Product partition model
Row effects model
Document Type: 
Working Paper

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