Academic Journal

A Comparative Study on Parameter Recovery of Three Approaches to Structural Equation Modeling.

Bibliographic Details
Title: A Comparative Study on Parameter Recovery of Three Approaches to Structural Equation Modeling.
Authors: Hwang, Heungsun1, Malhotra, Naresh K2, Kim, Youngchan3, Tomiuk, Marc A4, Hong, Sungjin5
Superior Title: Journal of Marketing Research (JMR). Aug2010, Vol. 47 Issue 4, p699-712. 14p. 1 Diagram, 3 Charts, 5 Graphs.
Subject Terms: *ANALYSIS of variance, *PARAMETER estimation, *MONTE Carlo method, *ERROR analysis in mathematics, *ANALYSIS of covariance, STRUCTURAL equation modeling, LEAST squares, COMPARATIVE studies, RESEARCH methodology evaluation, MODEL-based reasoning, STATISTICAL weighting, STATISTICAL bootstrapping
Abstract: Traditionally, two approaches have been employed for structural equation modeling: covariance structure analysis and partial least squares. A third alternative, generalized structured component analysis, was introduced recently in the psychometric literature. The authors conduct a simulation study to evaluate the relative performance of these three approaches in terms of parameter recovery under different experimental conditions of sample size, data distribution, and model specification. In this study, model specification is the only meaningful condition in differentiating the performance of the three approaches in parameter recovery. Specifically, when the model is correctly specified, covariance structure analysis tends to recover parameters better than the other two approaches. Conversely, when the model is misspecified, generalized structured component analysis tends to recover parameters better. Finally, partial least squares exhibits inferior performance in parameter recovery compared with the other approaches. In particular, this tendency is salient when the model involves cross-loadings. Thus, generalized structured component analysis may be a good alternative to partial least squares for structural equation modeling and is recommended over covariance structure analysis unless correct model specification is ensured. [ABSTRACT FROM AUTHOR]
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Database: Business Source Premier
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