Title: What's hampering measurement invariance: Detecting non-invariant items using clusterwise simultaneous component analysis
Authors: De Roover, Kim ×
Timmerman, Marieke
De Leersnyder, Jozefien
Mesquita, Batja
Ceulemans, Eva #
Issue Date: Apr-2014
Publisher: Frontiers Media S.A.
Series Title: Frontiers in Psychology vol:5
Article number: 604
Abstract: The issue of measurement invariance is ubiquitous in the behavioral sciences
nowadays as more and more studies yield multivariate multigroup data. When measurement
invariance cannot be established across groups, this is often due to different loadings on only
a few items. Within the multigroup CFA framework, methods have been proposed to trace
such non-invariant items, but these methods have some disadvantages in that they require
researchers to run a multitude of analyses and in that they imply assumptions that are often
questionable. In this paper, we propose an alternative strategy which builds on clusterwise
simultaneous component analysis (SCA). Clusterwise SCA, being an exploratory technique,
assigns the groups under study to a few clusters based on differences and similarities in the
covariance matrices, and thus based on the component structure of the items. Non-invariant
items can then be traced by comparing the cluster-specific component loadings via
congruence coefficients, which is far more parsimonious than comparing the component
structure of all separate groups. In this paper we present a heuristic for this procedure.
Afterwards, one can return to the multigroup CFA framework and check whether removing
the non-invariant items or removing some of the equality restrictions for these items, yields
satisfactory invariance test results. An empirical application concerning cross-cultural
emotion data is used to demonstrate that this novel approach is useful and can co-exist with
the traditional CFA approaches.
ISSN: 1664-1078
Publication status: published
KU Leuven publication type: IT
Appears in Collections:Social and Cultural Psychology
Methodology of Educational Sciences
× corresponding author
# (joint) last author

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