Dear Sir
The usual way for presenting PLSpredict results in a research article is as follows.

In the YouTube video tutorial, SEMinR Part-10 PLS Predict, we find RMSE (& MAE), LM-RMSE (& MAE), and PLS-LM, i.e., the difference between PLS-SEM analysis and LM benchmark.
The query is: Using R Studio, how can we separately determine the PLS Q2 _ predict values (as highlighted in the table) for constructs and indicators level?
Note: after running the model using R Studio, we got different attributes under predict_pls_model

SEMinR Part-10 PLS Predict: https://www.youtube.com/watch?v=h3Tw58fDRc0&t=905s
Thank you
Regards
Tushar
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Dear Sir,
Q: Is it feasible to utilize the cSEM package for computing PLS Q2 predict instead of the seminar package in that particular scenario?
Note:
> I utilized the seminr package to run PLSpredict and
obtained 'RMSE' scores with a negative sign for all item levels (only DVs), except for one item output below
>> Subsequently, when I processed the same dataset through the cSEM package, I obtained Q2_predict scores greater than zero for all item levels

>>> As of now, I have not come across any related references.
Thank you
Regards
Tushar
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