Abstract
| Original language | English |
|---|---|
| Pages (from-to) | 115-135 |
| Journal | Journal of the Academy of Marketing Science |
| Volume | 43 |
| Issue number | 1 |
| DOIs | |
| Publication status | Published - 2015 |
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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
Cite this
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A new criterion for assessing discriminant validity in variance-based structural equation modeling. / Henseler, Jörg; Ringle, Christian M.; Sarstedt, Marko.
In: Journal of the Academy of Marketing Science, Vol. 43, No. 1, 2015, p. 115-135.Research output: Contribution to journal › Article › Academic › peer-review
TY - JOUR
T1 - A new criterion for assessing discriminant validity in variance-based structural equation modeling
AU - Henseler, Jörg
AU - Ringle, Christian M.
AU - Sarstedt, Marko
N1 - Open access
PY - 2015
Y1 - 2015
N2 - 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.
AB - 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.
KW - IR-91561
KW - METIS-304728
KW - Structural equation modeling (SEM)
KW - Partial least squares (PLS)
KW - Results evaluation
KW - Measurement model assessment
KW - Discriminant validity
KW - Fornell-Larcker criterion
KW - Cross-loadings
KW - Multitrait-multimethod (MTMM) matrix
KW - Heterotrait-monotrait (HTMT) ratio of correlations
U2 - 10.1007/s11747-014-0403-8
DO - 10.1007/s11747-014-0403-8
M3 - Article
VL - 43
SP - 115
EP - 135
JO - Journal of the Academy of Marketing Science
JF - Journal of the Academy of Marketing Science
SN - 0092-0703
IS - 1
ER -