Analysis of multitrait-multimethod matrices: A two step principal components procedure

Stephen L. Golding, Edward Seidman

Research output: Contribution to journalArticle

Abstract

A relatively simple technique for assessing the convergence of sets of variables across method domains is presented. The technique, two-step principal components analysis, empirically orthogonalizes each method domain into sets of components, and then analyzes convergence among components across domains. The proposed technique is directly compared with Jackson's (1969) multi-method factor analysis (which involves an a priori orthogonalization) in the analysis of data from personality, vocational interest and aptitude domains. While Jackson's technique focuses on individual variables, and the two-step procedure focuses on the components of variable domains, both techniques produced evidence of cross-domain convergence. However, Jackson's method was found to have several undesirable mathematical and interpretational consequences, while the two-step procedure appears to be a promising technique for the systematic, empirical analysis of multitrait-multimethod matrices.

Original languageEnglish (US)
Pages (from-to)479-496
Number of pages18
JournalMultivariate Behavioral Research
Volume9
Issue number4
DOIs
StatePublished - 1974

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Principal Components
Orthogonalization
Aptitude
Empirical Analysis
Factor Analysis
Principal Component Analysis
Statistical Factor Analysis
Personality

ASJC Scopus subject areas

  • Arts and Humanities (miscellaneous)
  • Statistics and Probability
  • Experimental and Cognitive Psychology

Cite this

Analysis of multitrait-multimethod matrices : A two step principal components procedure. / Golding, Stephen L.; Seidman, Edward.

In: Multivariate Behavioral Research, Vol. 9, No. 4, 1974, p. 479-496.

Research output: Contribution to journalArticle

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