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The Analysis of Multitrait-Multimethod Matrices Via Constrained Components Analysis

Published online by Cambridge University Press:  01 January 2025

Henk A. L. Kiers ,
Yoshio Takane  and
Jos M. F. ten Berge
Henk A. L. Kiers*
Affiliation:
University of Groningen
Yoshio Takane
Affiliation:
McGill University
Jos M. F. ten Berge
Affiliation:
University of Groningen
*
Requests for reprints should be sent to Henk A.L. Kiers, Department of Psychology (SPA), Grote Kruisstraat 2/1, 9712 TS Groningen, THE NETHERLANDS.
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Abstract

Multitrait-Multimethod (MTMM) matrices are often analyzed by means of confirmatory factor analysis (CFA). However, fitting MTMM models often leads to improper solutions, or non-convergence. In an attempt to overcome these problems, various alternative CFA models have been proposed, but with none of these the problem of finding improper solutions was solved completely. In the present paper, an approach is proposed where improper solutions are ruled out altogether and convergence is guaranteed. The approach is based on constrained variants of components analysis (CA). Besides the fact that these methods do not give improper solutions, they have the advantage that they provide component scores which can later on be used to relate the components to external variables. The new methods are illustrated by means of simulated data, as well as empirical data sets.

Keywords

principal components analysiscommon factor analysisalternating least squares algorithmsidentificationuniquenesspartitioning of fit
Type
Original Paper
Information
Psychometrika , Volume 61 , Issue 4 , December 1996 , pp. 601 - 628
Copyright
Copyright © 1996 The Psychometric Society

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Footnotes

This research has been made possible by a fellowship from the Royal Netherlands Academy of Arts and Sciences to the first author. The authors are obliged to three anonymous reviewers and an associate editor for constructive suggestions on the first version of this paper.

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