Faculty of Economics and Business Administration Publications Database

Bayesian Analysis of the Heterogeneity Model

Selected
Authors:
Frühwirth-Schnatter, Sylvia
Tüchler, Regina
Source:
Volume: 22
Number: 1
Pages: 2 - 15
Month: January
ISSN-Print: 0735-0015
Link External Source: Online Version
Year: 2004
Keywords: Collapsing; Conjoint analysis; Grouping; Label switching; Mixture of random-effects model; Parameterization
Abstract:

We consider Bayesian estimation of a finite mixture of models with random effects, which is also known as the heterogeneity model. First, we discuss the properties of various Markov chain Monte Carlo samplers that are obtained from full conditional Gibbs sampling by grouping and collapsing. Whereas full conditional Gibbs sampling turns out to be sensitive to the parameterization chosen for the mean structure of the model, the alternative sampler is robust in this respect. However, the logical extension of the approach to the sampling of the group variances does not further increase the efficiency of the sampler. Second, we deal with the identifiability problem due to the arbitrary labeling within the model. Finally, a case study involving metric conjoint analysis serves as a practical illustration.

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