Bayesian clustering for row effects models |
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Authors: | Claudia Tarantola Guido Consonni Petros Dellaportas |
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Institution: | 1. Dipartimento di Economia Politica e Metodi Quantitativi, University of Pavia, Via S. Felice 7, 27100 Pavia, Italy;2. Athens University of Economics and Business, Athens, Greece |
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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 to enhance 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. |
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Keywords: | Clustering Contingency table Log-linear model Markov Chain Monte Carlo Mixture of Dirichlet process prior Partition Product partition model Row effects model |
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