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The Dependent Poisson Race Model and Modeling Dependence in Conjoint Choice Experiments

Published online by Cambridge University Press:  01 January 2025

Shiling Ruan ,
Steven N. MacEachern ,
Thomas Otter  and
Angela M. Dean
Shiling Ruan
Affiliation:
The Ohio State University
Steven N. MacEachern*
Affiliation:
The Ohio State University
Thomas Otter
Affiliation:
The Ohio State University
Angela M. Dean
Affiliation:
The Ohio State University
*
Requests for reprints should be sent to Steven N. MacEachern, Department of Statistics, The Ohio State University, Cockins Hall, Room 404, Columbus, OH 43210-1247, USA. E-mail: [email protected]
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Abstract

Conjoint choice experiments are used widely in marketing to study consumer preferences amongst alternative products. We develop a class of choice models, belonging to the class of Poisson race models, that describe a ‘random utility’ which lends itself to a process-based description of choice. The models incorporate a dependence structure which captures the relationship between the attributes of the choice alternatives and which appropriately moderates the randomness inherent in the race. The new models are applied to conjoint choice data and are shown to have performance markedly superior to that of independent Poisson race models and of the multinomial logit model.

Keywords

Bayesian modeldependent processesdominancemultinomial logit modelPoisson process
Type
Theory and Methods
Information
Psychometrika , Volume 73 , Issue 2 , June 2008 , pp. 261 - 288
Copyright
Copyright © 2007 The Psychometric Society

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Footnotes

This research was funded by the NSF under grant numbers SES-0437251 and DMS-0605041 and by the NSA under award number H98230-05-1-0065. The views expressed in this paper are those of the authors and are not necessarily those of the supporting institutions.

The authors would like to thank Trish Van Zandt, the Editor, Associate Editor, and Referees for their insightful comments.

Electronic Supplementary Material The online version of this article (http://dx.doi.org/10.1007/s11336-007-9035-y) contains supplementary material, which is available to authorized users.

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