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

Jörg Henseler, Christian M. Ringle, Marko Sarstedt

Journal of the Academy of Marketing Science · 2015 · Volume 43 · Issue 1

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.

Keywords

Structural equation modeling (SEM), Partial least squares (PLS), Results evaluation, Measurement model assessment, Discriminant validity, Fornell-Larcker criterion, Cross-loadings, Multitrait-multimethod (MTMM) matrix, Heterotrait-monotrait (HTMT) ratio of correlations

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