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Best, worst, and Best&worst choice probabilities for logit and reverse logit models

Author

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  • André de Palma

    (Université CYU, THEMA - Théorie économique, modélisation et applications - CNRS - Centre National de la Recherche Scientifique - CY - CY Cergy Paris Université)

  • Karim Kilani

    (LIRSA - Laboratoire interdisciplinaire de recherche en sciences de l'action - CNAM - Conservatoire National des Arts et Métiers [CNAM] - HESAM - HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université)

Abstract

This paper builds upon the work of Professor Marley, who, since the beginning of his long research career, has proposed rigorous axiomatics in the area of probabilistic choice models. Our study concentrates on models that can be applied to best and worst choice scaling experiments. We focus on those among these models that are based on strong assumptions about the underlying ranking of the alternatives with which the individual is assumed to be endowed when making the choice. Taking advantage of an inclusion-exclusion identity that we showed a few years ago, we propose a variety of best-worst choice probability models that could be implemented in software packages that are flourishing in this field.

Suggested Citation

  • André de Palma & Karim Kilani, 2022. "Best, worst, and Best&worst choice probabilities for logit and reverse logit models," Working Papers hal-03913928, HAL.
    • Handle: RePEc:hal:wpaper:hal-03913928
    Note: View the original document on HAL open archive server: https://cnam.hal.science/hal-03913928
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    References listed on IDEAS

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    1. Delle Site, Paolo & Kilani, Karim & Gatta, Valerio & Marcucci, Edoardo & de Palma, André, 2019. "Estimation of consistent Logit and Probit models using best, worst and best–worst choices," Transportation Research Part B: Methodological, Elsevier, vol. 128(C), pages 87-106.
    2. Hess, Stephane & Palma, David, 2019. "Apollo: A flexible, powerful and customisable freeware package for choice model estimation and application," Journal of choice modelling, Elsevier, vol. 32(C), pages 1-1.
    3. Anderson, Simon P. & de Palma, Andre, 1999. "Reverse discrete choice models," Regional Science and Urban Economics, Elsevier, vol. 29(6), pages 745-764, November.
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