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Path coefficients in PLS are usually standardized multivariate regression coefficients. Thus, they are the same as correlation coefficients if you have either just one IV or all IVs are orthogonal (uncorrelated). As soon as you have multiple correlated IVs they should not be the same, because the re...

If you assume that they both moderate the relationship you should also include both in the same model. Testing separate models would be prone to omitted variable bias.

We have not yet included a built-in feature for creating interaction effects. One way to do this in CB-SEM is create product-indicators for the new moderating construct. You can create these outside of the software and then import the dataset. But there are also other approaches and we are currently...

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No. From a methodological point of view the more the better (if you assume reflective measurement). This will increase precision and reliability of the estimated construct scores. However, asking many questions to respondents can be strenuous and make them less attentive to the questions, which may ...

In SmartPLS 4 you now have the option in the settings to select "unstandardized", which will provide unstandardized latent variable scores and model parameter.

If the moderator is binary, it has only the two values 0 and 1. Otherwise, if the moderator is continuous, it should also show the effect at -1.

For instrumental variable approaches there are guidelines for normal regression models on how to deal with interaction terms and nonlinear relationships. I would think that most of this also applies to endogeneity concerns in the structural model of PLS-SEM. A very good article is Papies, D., Ebbes,...

1. Yes. SmartPLS never standardizes the interaction term and always provides its unstandardized coefficients for them. 2. I am not sure, why it should be a problem to standardize the dependent variable. Dawson does not provide a sufficient argument in his paper why he believes that this is a problem...

You do not need to run IPMA anymore to get unstandardized LV scores. Simply select unstandardized in the PLS settings. You can then also export the unstandardized LV scores into a new dataset.

SmartPLS 4 does not contain Blindfolding anymore, because it is an outdated approach. If you want to do predictive model assessment, you should do PLSPredict.

Please see also https://www.smartpls.com/documentation/ ... indfolding

In general, if you have a continuous variable using a split (e.g., median split, or any other arbitrary split) is less reliable than using the original continuous variable as a moderator in the model. In your particular case, you may also end up with quite small groups that have low power to detect ...

When you hide zero values, then zero values are hidden. That might be useful for some results tables but not for all result tables. In SmartPLS 4 we have pre-specified in which tables zero values are hidden and in which tables they should be displayed. In general, SmartPLS 4 has many improvements an...

In step 3 you test whether the mean or variance difference is significantly different from zero. The permutation approach generates the reference distribution (random permuting the data into groups) from which you can generate confidence intervals for this reference distribution. Your mean or varian...

Thank you very much for the detailed information. We also already had a direct exchange in the SmartPLS support tool about this, pointing out that you are too quick to come to the alarming conclusion that it is a bug. That's more likely a misunderstanding. (1) In the SmartPLS data view (double click...