D-optimal conjoint choice designs with no-choice options for a nested logit model
Despite the fact that many conjoint choice experiments offer respondents a no-choice option in every choice set, the optimal design of conjoint choice experiments involving no-choice options has received only a limited amount of attention in the literature. In this article, we present an approach to construct D-optimal designs for this type of experiment. For that purpose, we derive the information matrix of a nested multinomial logit model that is appropriate for analyzing data from choice experiments with no-choice options. The newly derived information matrix is compared to the information matrix for the multinomial logit model that is used in the literature to construct designs for choice experiments. It is also used to quantify the loss of information in a choice experiment due to the presence of a no-choice option.
|Date of creation:||Dec 2008|
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- Zsolt Sándor & Michel Wedel, 2002. "Profile Construction in Experimental Choice Designs for Mixed Logit Models," Marketing Science, INFORMS, vol. 21(4), pages 455-475, February.
- Heiko Großmann & Heinz Holling & Ulrike Graßhoff & Rainer Schwabe, 2006. "Optimal Designs for Asymmetric Linear Paired Comparisons with a Profile Strength Constraint," Metrika, Springer, vol. 64(1), pages 109-119, August.
- Dhar, Ravi, 1997. " Consumer Preference for a No-Choice Option," Journal of Consumer Research, University of Chicago Press, vol. 24(2), pages 215-31, September.
- Kessels, Roselinde & Goos, Peter & Vandebroek, Martina, 2008. "Optimal designs for conjoint experiments," Computational Statistics & Data Analysis, Elsevier, vol. 52(5), pages 2369-2387, January.
- Kessels, Roselinde & Jones, Bradley & Goos, Peter & Vandebroek, Martina, 2009. "An Efficient Algorithm for Constructing Bayesian Optimal Choice Designs," Journal of Business & Economic Statistics, American Statistical Association, vol. 27(2), pages 279-291.
- Goos, Peter & Vandebroek, Martina, 2001. "-optimal response surface designs in the presence of random block effects," Computational Statistics & Data Analysis, Elsevier, vol. 37(4), pages 433-453, October.
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