Improving the efficiency of individualized designs for the mixed logit choice model by including covariates

Authors:
M. Crabbe;M. Vandebroek
Affiliations:
Katholieke Universiteit Leuven, Faculty of Business and Economics, Naamsestraat 69, 3000 Leuven, Belgium;Katholieke Universiteit Leuven, Faculty of Business and Economics, Naamsestraat 69, 3000 Leuven, Belgium and Leuven Statistics Research Center, W. de Croylaan 54, 3001 Leuven-Heverlee, Belgium
Venue:
Computational Statistics & Data Analysis
Year:
2012

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Abstract

Recent research shows that the inclusion of choice related demo- and sociographics in discrete choice models aids in modeling the choice behavior of consumers substantially. However, the increase in efficiency gained by accounting for covariates in the design of a choice experiment has thus far only been demonstrated for the conditional logit choice model. Previous findings are extended by using covariates in the construction of individualized Bayesian D-efficient designs for the mixed logit choice model. A simulation study illustrates how incorporating covariates affecting choice behavior yields more efficient designs and more accurate estimates and predictions at the individual level. Moreover, it is shown that the possible loss in design efficiency and therefore in estimation and prediction accuracy from including choice unrelated respondent characteristics is negligible.