Model-Robust Design of Conjoint Choice Experiments |
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Authors: | Jie Yu Peter Goos Martina Vandebroek |
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Affiliation: | 1. Faculty of Business and Economics , Katholieke Universiteit Leuven , Belgium Jie.Yu@econ.kuleuven.be;3. Faculty of Applied Economics , Universiteit Antwerpen , Antwerp, Belgium;4. Faculty of Business and Economics , Katholieke Universiteit Leuven , Belgium;5. Leuven Statistics Research Center , |
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Abstract: | Within the context of choice experimental designs, most authors have proposed designs for the multinomial logit model under the assumption that only the main effects matter. Very little attention has been paid to designs for attribute interaction models. In this article, three types of Bayesian D-optimal designs for the multinomial logit model are studied: main-effects designs, interaction-effects designs, and composite designs. Simulation studies are used to show that in situations where a researcher is not sure whether or not attribute interaction effects are present, it is best to take into account interactions in the design stage. In particular, it is shown that a composite design constructed by including an interaction-effects model and a main-effects model in the design criterion is most robust against misspecification of the underlying model when it comes to making precise predictions. |
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Keywords: | Bayesian D-optimal design Choice experimental designs Interaction effects Main effects Model-robust design |
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