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Yes it is possible, e. g. as a html report.

Best Regards

Christian

Hello Harez, there is a very interesting comment from Qureshi and Compeau on this topic. They said about the new method of Chin and Dibbern: “This method is new and not implemented in any PLS software. This “is probably way beyond what is expected in current research” and hence only one empirical st...

Your welcome! ad 1) Generally, only the interaction term (x*y) is used for interpretation (e.g. Henseler/Chin (2010), p. 85-86.) ad 2) Some authors argue, that the interaction coefficient shouldn’t the only basis for assessing the interaction effect, because the interaction coefficient could be bias...

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. T...

Dear Resoul! ad 1and 3) Your interaction term isn't significant because the t-value of x*y is <1,65. Therefore your moderating effect isn't significant and your hypothesis cannot supported. as 2) Normally we use the Effect Size for interpretation of changes in R2. ad 4) I don´t understand this quest...

SmartPLS delivere the t-values for the total effects after you have run a bootstrapping procedure.

Best regards
Christian

Forthermore you can find a good overview about evaluation of PLS Path Model results in Henseler/Ringle/Sinkovics (2009): The Use of Partial Least Squares in International Marketing, pp. 298-310.

Dear Claudia, your calculations with 500 bootstraps are o.k., but "the higher, the better". It is said, that higher bootstraps samples are less biased. Therefore it is better to use 1000. Furthermore your t-values 11,669 and 6,465 make sense. That mean that your path coefficients are high ...