000196057 001__ 196057
000196057 005__ 20180913062331.0
000196057 037__ $$aREP_WORK
000196057 245__ $$a Integrating psychometric indicators in latent class choice models
000196057 269__ $$a2013
000196057 260__ $$c2013
000196057 336__ $$aReports
000196057 520__ $$a Latent class models are a convenient and intuitive way to introduce taste heterogeneity in discrete choice models by relating attributes of the decision makers with unobserved behavioral classes, hence allowing for a more accurate market segmentation. Estimation and specification of latent class models can be improved with the use of psychometric indicators that measure the effect of unobserved attributes in the individual preferences. This paper proposes a method to introduce these additional indicators in the specification of integrated latent class and discrete choice models, through the definition of measurement equations that relate the indicators to attributes of the decision maker. The method is implemented for two mode-choice case studies and compared with alternative methods to introduce indicators. Results show that the proposed method generates significantly different estimates for the class and choice models and provide additional insight into the behavior of each class.
000196057 700__ $$0243036$$aHurtubia, Ricardo$$g184510
000196057 700__ $$aNguyen, My Hang
000196057 700__ $$0243045$$aGlerum, Aurélie$$g170790
000196057 700__ $$0240563$$aBierlaire, Michel$$g118332
000196057 8564_ $$s191003$$uhttps://infoscience.epfl.ch/record/196057/files/HuNgGlBi_2013.pdf$$yn/a$$zn/a
000196057 909C0 $$0252123$$pTRANSP-OR$$xU11418
000196057 909CO $$ooai:infoscience.tind.io:196057$$pENAC$$preport
000196057 937__ $$aEPFL-REPORT-196057
000196057 970__ $$aREP-HuNgGlBi_2013/TRANSP-OR
000196057 980__ $$aREPORT