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

André de Palma () and Karim Kilani
Additional contact information
André de Palma: 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]

Post-Print from HAL

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.

Keywords: Best-worst; scaling; experiments; Logit; model; Random; utility; models; Reverse; logit; model (search for similar items in EconPapers)
Date: 2023-12
References: Add references at CitEc
Citations:

Published in Journal of Choice Modelling, 2023, 49, pp.100449. ⟨10.1016/j.jocm.2023.100449⟩

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-04217535

DOI: 10.1016/j.jocm.2023.100449

Access Statistics for this paper

More papers in Post-Print from HAL
Bibliographic data for series maintained by CCSD ().