Dear PLS users,
Would anyone have some idea how to interpret Q-square results from SmartPLS blindfolding test? Do we look at the 1-SSE/SSO output or something else? Appreciate some tips/guidance.
Thanks
Q-square predictive relevance test
Q-square predictive relevance test
Mudiarasan Kuppusamy
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Dear Kuppusamy,
with Q-square you are testing the prediction relevance of your model. Q-square values above zero indicated that your values are well reconstructed and that the model has predictive relevance. You find the right output in SmartPLS at the “Construct Crossvalidated Redundancy” Output. There you have to look at the block with the “Total “ sums. However, as reported elsewhere in this forum, the blindfolding procedure has a bug at the actual release (s. viewtopic.php?t=944). You have pay attention to it. Further theoretical explanations for Q-square you can find in: Henseler, J./Ringle, C. M./Sinkovics, R. (2009): The Use of Partial Least Squares Path Modeling, in: Advances in International Marketing, Vol. 20 on pages 303 to 305.
I hope this helps!
Best regards
Christian
with Q-square you are testing the prediction relevance of your model. Q-square values above zero indicated that your values are well reconstructed and that the model has predictive relevance. You find the right output in SmartPLS at the “Construct Crossvalidated Redundancy” Output. There you have to look at the block with the “Total “ sums. However, as reported elsewhere in this forum, the blindfolding procedure has a bug at the actual release (s. viewtopic.php?t=944). You have pay attention to it. Further theoretical explanations for Q-square you can find in: Henseler, J./Ringle, C. M./Sinkovics, R. (2009): The Use of Partial Least Squares Path Modeling, in: Advances in International Marketing, Vol. 20 on pages 303 to 305.
I hope this helps!
Best regards
Christian
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- PLS Senior User
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Dear Christian,
Thank you for a great explaination
My questions are:
1. How many omission distance needs for running BF
2. I got a big number on TOTAL for every cases, it really more than 0
"Cross-validated R-square (i.e., Stone-Geisser’s Q2) between each endogenous latent variable and its own manifest variables can be calculated automatically in SmartPLS, Stone-Geisser’s Q2 by blindfolding and R2 by running the PLS procedure (Chatelin et al. 2002), and more than 0 is substantial..
Thanks
Thank you for a great explaination
My questions are:
1. How many omission distance needs for running BF
2. I got a big number on TOTAL for every cases, it really more than 0
"Cross-validated R-square (i.e., Stone-Geisser’s Q2) between each endogenous latent variable and its own manifest variables can be calculated automatically in SmartPLS, Stone-Geisser’s Q2 by blindfolding and R2 by running the PLS procedure (Chatelin et al. 2002), and more than 0 is substantial..
Thanks
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- PLS Expert User
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Please check following post:
viewtopic.php?t=1532&highlight=integer
There you can find some information about the omission distance.
Greetings,
Christian
viewtopic.php?t=1532&highlight=integer
There you can find some information about the omission distance.
Greetings,
Christian
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- PLS Senior User
- Posts: 28
- Joined: Thu Jun 24, 2010 5:38 am
- Real name and title:
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- PLS Expert User
- Posts: 248
- Joined: Sat Jul 25, 2009 1:34 pm
- Real name and title:
1 )what does cases mean here? I have data of 85 respondents and one of my Latent variable has 3 indicators (manifest variables). Then in this, what will be my omission distance.
2) What about Formative Latent Variables ( whos indicators are formative). Can I calculate Q^2 for this formative construct also.
3) what about my LV with only one indicator
2) What about Formative Latent Variables ( whos indicators are formative). Can I calculate Q^2 for this formative construct also.
3) what about my LV with only one indicator