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

Publikationstyp
Journal Article
Date Issued
2014-08-22
Sprache
English
Author(s)
Henseler, Jörg  
Ringle, Christian M.  orcid-logo
Sarstedt, Marko  
Institut
Personalwirtschaft und Arbeitsorganisation W-9  
TORE-URI
http://hdl.handle.net/11420/4026
Journal
Journal of the Academy of Marketing Science  
Volume
43
Issue
1
Start Page
115
End Page
135
Citation
Journal of the Academy of Marketing Science 43 (1): 115-135 (2014-08-22)
Publisher DOI
10.1007/s11747-014-0403-8
Scopus ID
2-s2.0-85028154911
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.
Subjects
Cross-loadings
Discriminant validity
Fornell-Larcker criterion
Heterotrait-monotrait (HTMT) ratio of correlations
Measurement model assessment
Multitrait-multimethod (MTMM) matrix
Partial least squares (PLS)
Results evaluation
Structural equation modeling (SEM)
DDC Class
000: Allgemeines, Wissenschaft
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