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The analysis of multitrait-multimethod matrices via constrained components analysis

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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.

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Authors and Affiliations

  1. University of Groningen, The Netherlands

    Henk A. L. Kiers & Jos M. F. ten Berge

  2. McGill University, Canada

    Yoshio Takane

Authors
  1. Henk A. L. Kiers
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  2. Yoshio Takane
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  3. Jos M. F. ten Berge
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Additional information

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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Kiers, H.A.L., Takane, Y. & ten Berge, J.M.F. The analysis of multitrait-multimethod matrices via constrained components analysis. Psychometrika 61, 601–628 (1996). https://doi.org/10.1007/BF02294039

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