Analysis of paired comparison data using Mx

Rung Ching Tsai*, Tsung Lin Wu

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

5 Citations (Scopus)


By postulating that the random utilities associated with the choice options follow a multivariate normal distribution, Thurstonian models (Thurstone, 1927) provide a straightforward representation of paired comparison data. The use of Monte Carlo Expectation-Maximization (MCEM) algorithms and limited information approaches have been proposed to overcome the estimation intractability in analyzing data with a large number of choice items. However, these approaches have not yet been implemented into standard statistical software. For paired comparison data with a medium number of items (≤6), it is possible to use the free software program Mx to obtain parameter estimates. This article shows how Mx can be used to obtain parameter estimates for Thurstonian paired comparison models. A number of simulations are conducted to assess its validity in obtaining the estimates in comparison to MCEM. In addition, 2 datasets are analyzed to demonstrate the use of MX in real applications.

Original languageEnglish
Pages (from-to)73-91
Number of pages19
JournalStructural Equation Modeling
Issue number1
Publication statusPublished - 2004

ASJC Scopus subject areas

  • General Decision Sciences
  • General Economics,Econometrics and Finance
  • Sociology and Political Science
  • Modelling and Simulation


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