How can I interpret my PLS-MIMIC model?

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sedabasar@yyu.edu.tr
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How can I interpret my PLS-MIMIC model?

Post by sedabasar@yyu.edu.tr »

I am a PhD student and I am studying PLS-MIMIC model. I have just one latent and two construct, one of them is formative and the other one is reflective. I have 10 indicators for formative construct, and 3 causes for reclective one . I am using SmartPLS 3. I understand I have just direct effect. Both indicators and causes have their loadings so how can I specify the relationship between causes and indicators?
jmbecker
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Re: How can I interpret my PLS-MIMIC model?

Post by jmbecker »

I don't quite understand the problem, but you might look into the PLS SEM book for redundancy analysis and also the following paper might help you:
Cheah, J. H., Sarstedt, M., Ringle, C. M., Ramayah, T., & Ting, H. (2018). Convergent validity assessment of formatively measured constructs in PLS-SEM: on using single-item versus multi-item measures in redundancy analyses. International Journal of Contemporary Hospitality Management, 30(11), 3192-3210.
Dr. Jan-Michael Becker, BI Norwegian Business School, SmartPLS Developer
Researchgate: https://www.researchgate.net/profile/Jan_Michael_Becker
GoogleScholar: http://scholar.google.de/citations?user ... AAAJ&hl=de
sedabasar@yyu.edu.tr
PLS Junior User
Posts: 2
Joined: Sun Feb 10, 2019 9:25 pm
Real name and title: Research Assistance Seda BAŞAR YILMAZ

Re: How can I interpret my PLS-MIMIC model?

Post by sedabasar@yyu.edu.tr »

I attached my model. I would lile to know that how I can know the relationships between eee and fff or ddd and hhh? Is it possible multiply their loadings of them to understand their(indicators) effects on causes)?
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jmbecker
SmartPLS Developer
Posts: 1282
Joined: Tue Mar 28, 2006 11:09 am
Real name and title: Dr. Jan-Michael Becker

Re: How can I interpret my PLS-MIMIC model?

Post by jmbecker »

Yes, you could multiply outer_weight*path_coefficient*outer_loading, e.g., 0.866*-0.371*0.833 = -0.268 for the effect of eee on fff in a sence of a total effect that matches partial regression coefficient logic.
Another option would be the use of outer_loading*path_coefficient*outer_loading, which would match a canonical correlation. You could find that also under Indicator Data (Correlations) > Model Implied Estimated Correlation Matrix
Dr. Jan-Michael Becker, BI Norwegian Business School, SmartPLS Developer
Researchgate: https://www.researchgate.net/profile/Jan_Michael_Becker
GoogleScholar: http://scholar.google.de/citations?user ... AAAJ&hl=de
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