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A practical approach to designing partial-profile choice experiments with two alternatives for estimating main effects and interactions of many two-level attributes

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  • Großmann, Heiko

Abstract

A method is presented which facilitates the practical construction of designs for stated choice experiments in which the choice sets are pairs of partial profiles and where, for a potentially large number of two-level attributes, the main effects and two-factor interactions are to be estimated. Although partly heuristic, the approach has a sound theoretical basis and can be used to generate utility-neutral designs for the multinomial logit model which possess a high statistical efficiency. Applying the method neither requires expert knowledge of design theory nor specialized software and is illustrated with several examples.

Suggested Citation

  • Großmann, Heiko, 2019. "A practical approach to designing partial-profile choice experiments with two alternatives for estimating main effects and interactions of many two-level attributes," Journal of choice modelling, Elsevier, vol. 32(C), pages 1-1.
    • Handle: RePEc:eee:eejocm:v:32:y:2019:i:c:1
    DOI: 10.1016/j.jocm.2018.04.001
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    References listed on IDEAS

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    1. John M. Rose & Michiel C.J. Bliemer, 2014. "Stated choice experimental design theory: the who, the what and the why," Chapters, in: Stephane Hess & Andrew Daly (ed.), Handbook of Choice Modelling, chapter 7, pages 152-177, Edward Elgar Publishing.
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    4. Palhazi Cuervo, Daniel & Kessels, Roselinde & Goos, Peter & Sörensen, Kenneth, 2016. "An integrated algorithm for the optimal design of stated choice experiments with partial profiles," Transportation Research Part B: Methodological, Elsevier, vol. 93(PA), pages 648-669.
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    9. Roselinde Kessels & Peter Goos & Bradley Jones & Martina Vandebroek, 2011. "Rejoinder: the usefulness of Bayesian optimal designs for discrete choice experiments," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 27(3), pages 197-203, May.
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