Comparing indirect effects in SEM: A sequential model fitting method using covariance-equivalent specifications
Publication in refereed journal

Times Cited
Web of Science13WOS source URL (as at 29/11/2020) Click here for the latest count
Altmetrics Information

Other information
AbstractIn social science research, an indirect effect occurs when the influence of an antecedent variable on the effect variable is mediated by an intervening variable. To compare indirect effects within a sample or across different samples, structural equation modeling (SEM) can be used if the computer program supports model fitting with nonlinear constraints. However, such an option is not routinely available in every popular software program. In this study, the basic idea of generating covariance-equivalent models in SEM is given and a sequential model fitting method is proposed as an alternative without the need to use nonlinear constraints. Under this method, the hypothesized model is transformed into a set of successive covariance-equivalent models so that an indirect effect is reparameterized as a single model parameter in the final transformed model. Real examples are given to illustrate how the proposed method is implemented using EQS, a SEM program that currently does not support the analysis with nonlinear constraints.
All Author(s) ListChan W
Journal nameStructural Equation Modeling
Volume Number14
Issue Number2
Pages326 - 346
LanguagesEnglish-United Kingdom
Web of Science Subject CategoriesMathematical Methods In Social Sciences; Mathematics; Mathematics, Interdisciplinary Applications; MATHEMATICS, INTERDISCIPLINARY APPLICATIONS; Social Sciences, Mathematical Methods; SOCIAL SCIENCES, MATHEMATICAL METHODS

Last updated on 2020-30-11 at 00:14