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A multi-level cross-classified model for discrete response variables

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  • Bhat, Chandra R.
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    Abstract

    In many spatial analysis contexts, the variable of interest is discrete and there is spatial clustering of observations. This paper formulates a model that accommodates clustering along more than one dimension in the context of a discrete response variable. For example, in a travel mode choice context, individuals are clustered by both the home zone in which they live as well as by their work locations. The model formulation takes the form of a mixed logit structure and is estimated by maximum likelihood using a combination of Gaussian quadrature and quasi-Monte Carlo simulation techniques. An application to travel mode choice suggests that ignoring the spatial context in which individuals make mode choice decisions can lead to an inferior data fit as well as provide inconsistent evaluations of transportation policy measures.

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    File URL: http://www.sciencedirect.com/science/article/B6V99-40B847Y-2/2/9477cb4d9622edbe66914efa0f5daf8b
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    Bibliographic Info

    Article provided by Elsevier in its journal Transportation Research Part B: Methodological.

    Volume (Year): 34 (2000)
    Issue (Month): 7 (September)
    Pages: 567-582

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    Handle: RePEc:eee:transb:v:34:y:2000:i:7:p:567-582

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    Cited by:
    1. Makoto Chikaraishi & Akimasa Fujiwara & Junyi Zhang & Kay Axhausen, 2011. "Identifying variations and co-variations in discrete choice models," Transportation, Springer, vol. 38(6), pages 993-1016, November.
    2. Stephane Hess & John W. Polak, 2004. "An analysis of parking behaviour using discrete choice models calibrated on SP datasets," ERSA conference papers ersa04p60, European Regional Science Association.
    3. Chandra Bhat & Ipek Sener, 2009. "A copula-based closed-form binary logit choice model for accommodating spatial correlation across observational units," Journal of Geographical Systems, Springer, vol. 11(3), pages 243-272, September.
    4. Jie Lin & Liang Long, 2008. "What neighborhood are you in? Empirical findings of relationships between household travel and neighborhood characteristics," Transportation, Springer, vol. 35(6), pages 739-758, November.
    5. Konstadinos Goulias, 2002. "Multilevel analysis of daily time use and time allocation to activity types accounting for complex covariance structures using correlated random effects," Transportation, Springer, vol. 29(1), pages 31-48, February.

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