Analysis of paired comparison data using Mx

Rung Ching Tsai; Tsung Lin Wu

doi:10.1207/S15328007SEM1101_6

Analysis of paired comparison data using Mx

Rung Ching Tsai^*
, Tsung Lin Wu

^*Corresponding author for this work

Department of Mathematics

Research output: Contribution to journal › Article › peer-review

5 Citations (Scopus)

Abstract

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 language	English
Pages (from-to)	73-91
Number of pages	19
Journal	Structural Equation Modeling
Volume	11
Issue number	1
DOIs	https://doi.org/10.1207/S15328007SEM1101_6
Publication status	Published - 2004

ASJC Scopus subject areas

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

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Cite this

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Analysis of paired comparison data using Mx

Abstract

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