A New Criterion for Assessing Discriminant Validity in Variance-Based Structural Equation Modeling

Journal of the Academy of Marketing Science (JAMS), Vol. 43, No. 1, pp. 115-135, 2015

Posted: 14 Jun 2017

See all articles by Jörg Henseler

Jörg Henseler

Institute for Management Research, Radboud University Nijmegen; Instituto Superior de Estatística e Gestão de Informação, Universidade Nova de Lisboa

Christian M. Ringle

Hamburg University of Technology (TUHH)

Marko Sarstedt

Otto-von-Guericke-Universität Magdeburg; Otto-von-Guericke-Universität Magdeburg; University of Newcastle (Australia)

Date Written: March 18, 2014

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 equationmodeling (SEM), Partial least squares (PLS), Results evaluation, Measurementmodel assessment, Discriminantvalidity, Fornell-Larckercriterion, Cross-loadings, Multitrait-multimethod (MTMM)matrix, Heterotrait-monotrait (HTMT) ratio of correlations

Suggested Citation

Henseler, Jörg and Ringle, Christian M. and Sarstedt, Marko, A New Criterion for Assessing Discriminant Validity in Variance-Based Structural Equation Modeling (March 18, 2014). Journal of the Academy of Marketing Science (JAMS), Vol. 43, No. 1, pp. 115-135, 2015, Available at SSRN: https://ssrn.com/abstract=2985343

Jörg Henseler

Institute for Management Research, Radboud University Nijmegen ( email )

Thomas van Aquinostraat 3
P.O. Box 9108
Nijmegen, 6500HK
Netherlands
+31 24 3611854 (Phone)
+31 24 3611933 (Fax)

HOME PAGE: http://www.ru.nl/fm/henseler

Instituto Superior de Estatística e Gestão de Informação, Universidade Nova de Lisboa ( email )

Campus de Campolide
Lisbon, 1070-312
Portugal

HOME PAGE: http://www.henseler.com

Christian M. Ringle (Contact Author)

Hamburg University of Technology (TUHH) ( email )

Am Schwarzenberg-Campus 4
Hamburg, 21073
Germany

HOME PAGE: http://www.tuhh.de/hrmo

Marko Sarstedt

Otto-von-Guericke-Universität Magdeburg ( email )

Universitätspl. 2
PSF 4120
Magdeburg, D-39106
Germany

Otto-von-Guericke-Universität Magdeburg ( email )

Universitätspl. 2
PSF 4120
Magdeburg, D-39106
Germany

University of Newcastle (Australia) ( email )

University Drive
Callaghan, NSW 2308
Australia

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