A new criterion for assessing discriminant validity in variance-based structural equation modeling

Discriminant validity assessment has become a generally accepted prerequisite for analyzing relationships between latent variables. For variance-based structural equation modeling, such as partial least squares, the Fornell-Larcker criterion and the examination of cross-loadings are the dominant app...

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Bibliographic Details
Published in:Journal of the Academy of Marketing Science 2015-01, Vol.43 (1), p.115-135
Main Authors: Henseler, Jörg, Ringle, Christian M., Sarstedt, Marko
Format: Article
Language:English
Subjects:
Analysis
Business and Management
Discriminant analysis
Economic models
Marketing
Methodological Paper
Monte Carlo simulation
Research methodology
Researchers
Social Sciences
Strategic management
Structural equation modeling
Studies
Validation studies
Validity
Variables
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Summary:Discriminant validity assessment has become a generally accepted prerequisite for analyzing relationships between latent variables. For variance-based structural equation modeling, such as partial least squares, the Fornell-Larcker criterion and the examination of cross-loadings are the dominant approaches for evaluating discriminant validity. By means of a simulation study, we show that these approaches do not reliably detect the lack of discriminant validity in common research situations. We therefore propose an alternative approach, based on the multitrait-multimethod matrix, to assess discriminant validity: the heterotrait-monotrait ratio of correlations. We demonstrate its superior performance by means of a Monte Carlo simulation study, in which we compare the new approach to the Fornell-Larcker criterion and the assessment of (partial) cross-loadings. Finally, we provide guidelines on how to handle discriminant validity issues in variance-based structural equation modeling.
ISSN:0092-0703
1552-7824
DOI:10.1007/s11747-014-0403-8