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.
Original language | English |
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Pages (from-to) | 115-135 |
Journal | Journal of the Academy of Marketing Science |
Volume | 43 |
Issue number | 1 |
DOIs | |
Publication status | Published - 2015 |
Keywords
- IR-91561
- METIS-304728
- 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