The usefulness of Bayesian optimal designs for discrete choice experiments |
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Authors: | Roselinde Kessels Bradley Jones Peter Goos Martina Vandebroek |
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Affiliation: | 1. Faculty of Applied Economics and StatUa Center for Statistics, Universiteit Antwerpen, , 2000 Antwerp, Belgium;2. SAS Institute Inc., SAS Campus Drive, , Cary, NC 27513 USA;3. Erasmus School of Economics, Erasmus Universiteit Rotterdam, , 3000 DR Rotterdam, The Netherlands;4. Faculty of Business and Economics, Katholieke Universiteit Leuven, , 3000 Leuven, Belgium;5. Leuven Statistics Research Center, Katholieke Universiteit Leuven, , 3001 Leuven‐Heverlee, Belgium |
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Abstract: | Recently, the use of Bayesian optimal designs for discrete choice experiments, also called stated choice experiments or conjoint choice experiments, has gained much attention, stimulating the development of Bayesian choice design algorithms. Characteristic for the Bayesian design strategy is that it incorporates the available information about people's preferences for various product attributes in the choice design. This is in contrast with the linear design methodology, which is also used in discrete choice design and which depends for any claims of optimality on the unrealistic assumption that people have no preference for any of the attribute levels. Although linear design principles have often been used to construct discrete choice experiments, we show using an extensive case study that the resulting utility‐neutral optimal designs are not competitive with Bayesian optimal designs for estimation purposes. Copyright © 2011 John Wiley & Sons, Ltd. |
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Keywords: | choice experiments stated choice data Bayesian design utility‐neutral or linear design orthogonal design D‐optimality |
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