Comparing designs for choice experiments: A case study

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dc.contributor.author Burgess, Leonie en_US
dc.contributor.author Street, Deborah en_US
dc.contributor.author Wasi, Nada en_US
dc.contributor.editor en_US
dc.date.accessioned 2012-10-12T03:32:48Z
dc.date.available 2012-10-12T03:32:48Z
dc.date.issued 2011 en_US
dc.identifier 2011000904 en_US
dc.identifier.citation Burgess Leonie, Street Deborah, and Wasi Nada 2011, 'Comparing designs for choice experiments: A case study', Grace Scientific Publishing, vol. 5, no. 1, pp. 25-46. en_US
dc.identifier.issn 1559-8608 en_US
dc.identifier.other C1 en_US
dc.identifier.uri http://hdl.handle.net/10453/17943
dc.description.abstract This paper describes an empirical comparison of the performance of four designs for a discrete choice experiment. These designs were chosen to represent the range of construction techniques that are currently popular for choice experiments when no prior knowledge of the parameters is available. Each design had 320 respondents who each completed 16 choice sets. The results suggest that for the multinomial logit model (MNL) the design that is used at this stage is fairly unimportant. As the sample size gets smaller, however, differences between the designs become apparent. We also analysed the results using four different models which accommodate preference heterogeneity. We find that any of these models are able to predict choices more accurately for born in-sample and out-of-sample than the MNL model for the designs used here, and that the differences across designs arc larger for models with more parameters, although preliminary results suggest the gain appears to depend on the underlying preference structure. en_US
dc.language en_US
dc.publisher Grace Scientific Publishing en_US
dc.relation.isbasedon http://dx.doi.org/10.1080/15598608.2011.10412048 en_US
dc.title Comparing designs for choice experiments: A case study en_US
dc.parent Journal of Statistical Theory and Practice en_US
dc.journal.volume 5 en_US
dc.journal.number 1 en_US
dc.publocation United States en_US
dc.identifier.startpage 25 en_US
dc.identifier.endpage 46 en_US
dc.cauo.name SCI.Mathematical Sciences en_US
dc.conference Verified OK en_US
dc.for 010400 en_US
dc.personcode 960812 en_US
dc.personcode 950324 en_US
dc.personcode 996634 en_US
dc.percentage 100 en_US
dc.classification.name Statistics en_US
dc.classification.type FOR-08 en_US
dc.edition en_US
dc.custom en_US
dc.date.activity en_US
dc.location.activity en_US
dc.description.keywords MNL model, GMNL model, Mixed logit, Stated preference experiments en_US
dc.staffid en_US
dc.staffid 996634 en_US


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