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We did not follow-up on this direction. As as work around, you may extract the unstandardized latent variable scores from the IPMA results report and run a "standard multilevel analysis" for the partial regression models.

Thanks. Use the one or the other approach but with 5,000 bootstrap samples. However, your upper bound is above 1 which means that discriminant validity has not been established. Your confidence intervals are very wide. I suppose that you use a small sample (which would be a data problem) and/or a fu...

You would like to do a one-sided test (or use a 10% probability of error with the 2-sided test) to obtain the upper bound at the 95% point (and not at 97.5%.

You may exclude the potential explanatory variables form the model before running FIMIX-PLS. @FIMIX-PLS and segmentation: The book on advanced PLS-SEM issues by Hair et al. (2018) has a chapter on this topic: https://www.smartpls.com/documentation/learn-pls-sem-and-smartpls/book-on-advanced-pls-sem-...

Thanks. To get started on second-order models, you may want to take a look at the respective chapter in the book advanced PLS-SEM issues by Hair et al. (2018): https://www.smartpls.com/documentation/learn-pls-sem-and-smartpls/book-on-advanced-pls-sem-issues "To begin with, in my Ph.D. thesis model, ...

Just double-click on the data-set in SmartPLS 3.

Well, it's a little bit high. Can you get it below 0.9? Otherwise, bootstrap the HTMT (use complete bootstrapping in SmartPLS 3) and show that the HTMT is significantly lower than 1 (look at the upper bound of HTMT's bootstrap confidence interval).

Best
Christian

This is not a PLS-specific but general concern. Please search for articles, books, and webpages that address the multiple testing issues. In multiple testing situations, we need to adjust the accepted probability of error level. When using the Bonferroni correction to account for 6 comparisons, the ...

Then, you established partial invariance and can compare the standardized group-specific coefficients: https://www.emeraldinsight.com/doi/abs/ ... -2014-0304

Just include the moderator variable in your model, select the target construct, right-click and select the "Add interaction term" option. Here, you find a chapter on moderation in PLS-SEM: https://www.smartpls.com/documentation/learn-pls-sem-and-smartpls/pls-sem-book Also take a look at this article...

Please upload a screenshot of your model (with results) and the PLSpredict results table.

In principle, you are on the right track. In the second edition of the book, the explications have been slightly modified. Here, one looks at an effect size level and the required sample size. The attached pictures provide further explications. Please note that these are technical considerations. Re...

A rho_A value above 1 is strange and should not occur. You may revert to Cronbach's alpha in that case.

When the data export from SPSS includes such values "4,64E+09", SmartPLS 3 cannot correctly read the data file. "E" is a string and SmartPLS 3 only expects values. The rule for SmartPLS data: Only use text in the first row (i.e., the header which contains the variable names); sometimes, we also expe...

Thanks. Usually, you only need to assess discriminant validity for two and more reflective constructs in a PLS path model.

Best
CR