Hello everyone,
I ran the PLS SEM for effect size f2 and q2 and found it a little odd. Is it possible to have an inverse outcome between the explanatory power (f2) and predictive power (q2). For e.g:
Factor A f2 = 0.36, q2 = 0.12
Factor B f2 = 0.25, q2 = 0.15
Factor C f2 = 0.08, q2 = 0.21
Factor D f2 = 0.03, q2 = 0.26
How is it possible to get a low explanatory power, but high predictive power and vice versa? If it is not possible, where did I went wrong with the analysis? Feedbacks are greatly appreciated. Thanks.
f2 and q2
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- SmartPLS Developer
- Posts: 1287
- Joined: Tue Mar 28, 2006 11:09 am
- Real name and title: Dr. Jan-Michael Becker
Re: f2 and q2
First, I would try to replicate the finding with PLSPredict. It has a much better foundation than the Blindfolding which is a method developed in the 1980s.
Second, it is generally possible if the factors with high explanatory power lead to overfitting. However, such consistency of inverse results would also be suspicious to me.
Second, it is generally possible if the factors with high explanatory power lead to overfitting. However, such consistency of inverse results would also be suspicious to me.
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
Researchgate: https://www.researchgate.net/profile/Jan_Michael_Becker
GoogleScholar: http://scholar.google.de/citations?user ... AAAJ&hl=de
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- PLS Junior User
- Posts: 3
- Joined: Wed Jun 12, 2019 4:52 am
- Real name and title: Noman Mahmood
Re: f2 and q2
Dear jmbecker,
Is there any other way to calculate effect size (f2) for formative second order constructs. R2 is equal to 0.99999 (1.00).
Computed F2 in SmartPLS are too big because of it.
Is there any other way to calculate effect size (f2) for formative second order constructs. R2 is equal to 0.99999 (1.00).
Computed F2 in SmartPLS are too big because of it.