Comparing squared multiple correlation coefficients using structural equation modeling

Research output: Contribution to journalArticles

2 Citations (Scopus)

Abstract

In social science research, a common topic in multiple regression analysis is to compare the squared multiple correlation coefficients in different populations. Existing methods based on asymptotic theories (Olkin & Finn, 1995) and bootstrapping (Chan, 2009) are available but these can only handle a 2-group comparison. Another method based on structural equation modeling (SEM) has been proposed recently. However, this method has three disadvantages. First, it requires the user to explicitly specify the sample R2 as a function in terms of the basic SEM model parameters, which is sometimes troublesome and error prone. Second, it requires the specification of nonlinear constraints, which is not available in some popular SEM software programs. Third, it is for a 2-group comparison primarily. In this article, a 2-stage SEM method is proposed as an alternative. Unlike all other existing methods, the proposed method is simple to use, and it does not require any specific programming features such as the specification of nonlinear constraints. More important, the method allows a simultaneous comparison of 3 or more groups. A real example is given to illustrate the proposed method using EQS, a popular SEM software program. Copyright © 2014 Taylor & Francis Group.
Original languageEnglish
Pages (from-to)225-238
JournalStructural Equation Modeling: A Multidisciplinary Journal
Volume21
Issue number2
Early online dateApr 2014
DOIs
Publication statusPublished - 2014

Citation

Kwan, J. L. Y., & Chan, W. (2014). Comparing squared multiple correlation coefficients using structural equation modeling. Structural Equation Modeling: A Multidisciplinary Journal, 21(2), 225-238.

Keywords

  • Squared multiple correlation coefficients
  • Structural equation modeling
  • Model reparameterization
  • Multi-sample analysis

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