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Conditional parameter estimates from Mixed Logit models: distributional assumptions and a free software tool

Hess, S (2010) Conditional parameter estimates from Mixed Logit models: distributional assumptions and a free software tool. Journal of Choice Modelling, 3 (2). 134 - 152 . ISSN 1755-5345

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Abstract

A number of authors have discussed the possible advantages of conditioning parameter distributions on observed choices when working with Mixed Multinomial Logit models. However, the number of applications is still relatively small, partly due to a limited implementation in available software. To address this situation, the present paper discusses the development of a freeware software tool that allows users to compute conditional distributions independently of the software used during model estimation. Additionally, the paper looks at what impact assumptions made for the unconditional distributions have on the results obtained with conditional distributions. Here, an application using stated choice data collected in Denmark shows that while the move from unconditional to conditional distributions possibly brings results closer together, some discrepancies do remain.

Item Type: Article
Copyright, Publisher and Additional Information: © 2010 Hess. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Institution: The University of Leeds
Academic Units: The University of Leeds > Faculty of Environment (Leeds) > Institute for Transport Studies (Leeds)
Depositing User: Symplectic Publications
Date Deposited: 28 May 2012 09:16
Last Modified: 08 Jun 2014 04:52
Status: Published
Publisher: University of Leeds
Refereed: Yes
URI: http://eprints.whiterose.ac.uk/id/eprint/43620

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