Analysis of Paired Comparison Data Using Monte Carlo EM Algorithms

Representations of Thurstonian models cannot be uniquely identified because of the discrete nature and the difference structure of the paired comparison data. In this thesis, the identifiability of model parameters are investigated by studying empirically equivalent Thurstonian models. Equivalence relations and their implications on interpretation are presented in detail for a number of covariance structures. Wherever possible, specific conditions are given to allow researchers to examine the identifiability of the model parameters.

Name thesis:degree_name

Ph.D.

Level thesis:degree_level

Dissertation

Discipline thesis:degree_discipline

Psychology

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2015

Author dc:creator

• Tsai, Rung-Ching

Contributors dc:contributor

• Bockenholt, Ulf

• Statistics

Language dc:language

eng

Identifier

(MiAaPQ)AAI3023219

OAI identifier oai:identifier

oai:www.ideals.illinois.edu:2142/82013