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

Other free copies

• hdl.handle.netPublished version · Web page
• ris.utwente.nlAccepted manuscript · PDF
• Figshare (United Kingdom) (figshare.com)Preprint · Web page
• University of Newcastle Australia (hdl.handle.net)Preprint · Web page
• research.utwente.nlPreprint · Web page

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.