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Generalized Structured Component Analysis

Published online by Cambridge University Press:  01 January 2025

Heungsun Hwang  and
Yoshio Takane
Heungsun Hwang*
Affiliation:
HEC Montreal
Yoshio Takane
Affiliation:
McGill University
*
Requests for reprints should be addressed to: Heungsun Hwang, HEC Montreal, Department of Marketing, 3000 Chemin de la Cole Ste-Calherine, Montreal, Quebec, H3T 2A7, CANADA. Email: [email protected]
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Abstract

We propose an alternative method to partial least squares for path analysis with components, called generalized structured component analysis. The proposed method replaces factors by exact linear combinations of observed variables. It employs a well-defined least squares criterion to estimate model parameters. As a result, the proposed method avoids the principal limitation of partial least squares (i.e., the lack of a global optimization procedure) while fully retaining all the advantages of partial least squares (e.g., less restricted distributional assumptions and no improper solutions). The method is also versatile enough to capture complex relationships among variables, including higher-order components and multi-group comparisons. A straightforward estimation algorithm is developed to minimize the criterion.

Keywords

Path analysis with componentspartial least squaresalternating least squares
Type
Theory And Methods
Information
Psychometrika , Volume 69 , Issue 1 , March 2004 , pp. 81 - 99
Copyright
Copyright © 2004 The Psychometric Society

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Footnotes

The work reported in this paper was supported by Grant A6394 from the Natural Sciences and Engineering Research Council of Canada to the second author. We wish to thank Richard Bagozzi for permitting us to use his organizational identification data and Wynne Chin for providing PLS-Graph 3.0.

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