Template-Type: ReDIF-Paper 1.0
Author-Name: Lam, K.Y.
Author-Name-Last: Lam
Author-Name-First: Kar Yin
Author-Name: Koning, A.J.
Author-Name-Last: Koning
Author-Name-First: Alex
Author-Name: Franses, Ph.H.B.F.
Author-Name-Last: Franses
Author-Name-First: Philip Hans
Author-Person: pfr226
Title: Ranking Models in Conjoint Analysis
Abstract: In this paper we consider the estimation of probabilistic
 ranking models in the context of conjoint experiments. By using
 approximate rather than exact ranking probabilities, we do not
 need to compute high-dimensional integrals. We extend the
 approximation technique proposed by \\citet{Henery1981} in the
 Thurstone-Mosteller-Daniels model for any Thurstone order
 statistics model and we show that our approach allows for a
 unified approach. Moreover, our approach also allows for the
 analysis of any partial ranking. Partial rankings are essential
 in practical conjoint analysis to collect data efficiently to
 relieve respondents' task burden.
Creation-Date: 2010-10-12
File-URL: https://repub.eur.nl/pub/20937/EI2010-51.pdf
File-Format: application/pdf
Series: RePEc:ems:eureir
Number: EI 2010-51
Keywords: conjoint experiments, partial rankings, thurstone order statistics model
Handle: RePEc:ems:eureir:20937