If I have a model with multiple DVs, should I test the discriminant validity of my variables with all DVs included at the same time? The reason I ask is because each DV yields a separate model, and thus multiple DVs are not estimated 'simultaneously' - they can be in the software, but statistically they are independent.
So under this circumstance, is it relevant to test the discriminant validity of DVs that are in statistically independent models but part of the same study and have the same set of IVs? I.e., do I really care if the DVs in different models are sufficiently distinct?
Discriminant validity with multiple DVs
- cringle
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Re: Discriminant validity with multiple DVs
You may want to test discriminant validity for all construct in the model at the same time. Use the HTMT cirterion: Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A New Criterion for Assessing Discriminant Validity in Variance-based Structural Equation Modeling. Journal of the Academy of Marketing Science, 43(1), 115-135. https://www.youtube.com/channel/UCW4GA7 ... sCgSDLuo1Q
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CR
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CR
Prof. Dr. Christian M. Ringle, Hamburg University of Technology (TUHH), SmartPLS
- Literature on PLS-SEM: https://www.smartpls.com/documentation
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- Literature on PLS-SEM: https://www.smartpls.com/documentation
- Google Scholar: https://scholar.google.de/citations?use ... AAAJ&hl=de