A Modified Tucker’s Congruence Coefficient for Factor Matching

Authors

  • Anikó Lovik
    I-BioStat, KU Leuven - University of Leuven, Leuven, Belgium
  • Vahid Nassiri
    I-BioStat, KU Leuven - University of Leuven, Leuven, Belgium; OpenAnalytics, Antwerp, Belgium
  • Geert Verbeke
    I-BioStat, KU Leuven - University of Leuven, Leuven, Belgium; I-BioStat, Hasselt University, Hasselt, Belgium
  • Geert Molenberghs
    I-BioStat, KU Leuven - University of Leuven, Leuven, Belgium; I-BioStat, Hasselt University, Hasselt, Belgium

Abstract

Since factor analysis is one of the most often used techniques in psychometrics, comparing or combining solutions from different factor analyses is often needed. Several measures to compare factors exist, one of the best known is Tucker’s congruence coefficient, which is enjoying newly found popularity thanks to the recent work of Lorenzo-Seva and ten Berge (2006), who established cut-off values for factor congruence. While this coefficient is in most cases very good in comparing factors in general, it also has some disadvantages, which can cause trouble when one needs to compare or combine many analyses. In this paper, we propose a modified Tucker’s congruence coefficient to address these issues.