A new criterion for assessing discriminant validity in variance-based structural equation modeling
Abstract
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.
Cite this
Jörg Henseler, Christian M. Ringle, Marko Sarstedt (2014). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science. https://doi.org/10.1007/s11747-014-0403-8
@article{jrg2014a,
title = {A new criterion for assessing discriminant validity in variance-based structural equation modeling},
author = {Henseler, Jörg and Ringle, Christian M. and Sarstedt, Marko},
year = {2014},
journal = {Journal of the Academy of Marketing Science},
doi = {10.1007/s11747-014-0403-8}
}Citations in this library
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