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Dear Sergeja, if your formative LV only has one indicator, things are not that difficult. Simply standardize your 4 indicators (f1, r1, r2, r3) and create 3 product-interaction-indicators (f1*r1, f1*r2, f1*r3) prior to loading the data into SmartPLS. You can then use the reflective mode to create an...

Hi all, I agree. The only way to do this in SmartPLS is to create an LV (bubble) for each indicator (square). Since the loading and weight will always be 1, it doesn't even matter whether you choose a reflective or formative measurement mode. However, if all your variables are measured by a single i...

Hi Sandra, given that - at a structural level - PLS is just a multiple regression between latent variables, your test should work. While the covariance of coefficients is not reported by SmartPLS, you could simply export the path coefficient data from the bootstrap report to Excel and then calculate...

Hi Stefan, first of all, Chin's rule of thumb is only just that - a rule of thumb. If you want to dig deeper into sample size requirements, you have to do the following: 1) Define your structural/ measurement models 2) Form hypotheses about effect sizes of your predictors 3) Define an acceptable pow...

Oliver, now we're really delving into the issues... ;-) Some comments on your comments: (A) Weight changes in independent LVs Let me clarify my earlier post a little bit here. I was not saying that any change (even the slightest) in the indicator weights is necessarily problematic. I was simply sayi...

Oliver, I'm struggling with similar issues in my path model. Not that I'm any closer to a definitive answer to your questions, but here's my current thinking on the available options: (A) Singling out the effect into a simple 4 LV-PLS-model: Y=b1*X+b2*Z+b3*X*Z This is only valid if the indicator wei...

Matthias,

what you are describing sounds like an extreme case. Can you let us know some more parameters? E.g.

- original sample size
- bootstrap sample size
- number of bootstrap runs
- path estimate (original & bootstrap)
- bootstrap standard deviation


Cheers,
Stefan

Hi Christian, thank you for pointing this out (SE=Bootstrap Stdev). This certainly explains why the formula didn't work earlier. However, I'm still not sure how to properly apply the formula. In particular, I have found two different versions of the formula: Version 1 (from Chin's homepage): S_Poole...

Jörg/ Christian, thank you both for your helpful comments. Chin's suggested approach for using bootstrap parameters in a parametric sense is actually what I tried first. However, his formula gave me very high t-values even for the smallest coefficient differences (e.g., t=18.3 for a path difference ...

Hi Sven, so this confirms my hypothesis about the randomization issue. Given today's computer power, I would propose to go with the "more random" way of generating the random numbers. However, if you wanted to put icing on the cake, you could make it optional somewhere in the settings ;-) ...

Dear Sven, thanks for looking into this so quickly. However, I'm still not convinced that the problem you described is cause for the resample-duplications. I just opened SmartPLS fresh from the Start Menu. Then I opened my simple path model (see above) and ran a bootstrap. Looking at the results sti...

All, since nobody has answered my post, I had to find a way to solve this myself ;-). I'm posting the procedure here for anyone who is interested (feedback highly welcome): A) run the model with the full data set in PLS and save the LV-scores B) split the file with the LV-scores into two subgroups y...

Christian, I am aware of the functioning of the algorithm in principle. However, the "randomness" of the case selection in the resampling is essential here. Knowing that it is impossible for a computer program to produce truly random numbers, I am pointing out a weakness in the pseudo-rand...

Dear Development Team, I think I may have discovered an issue with the bootstrap estimates for very simple path models on fast computers: Apparently, the seed for the random number generator (RNG) used to select cases for the bootstrap samples does not always change from run to run. I suspect that s...

Christian, great news! I would certainly like to see the following way of calculating interaction indicators implemented in the next release: 1. Standardize indicators for A and B 2. Create interaction indicators for A*B (multiplying standardized scores) 3. Run PLS Model This would be true to the pr...