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Hi

1 user = 1 key = 3 instalations (different PCs)

Best regards,
Bido

Hi Hussain, 1) Yes, t > 1.96, path is significant, hypothesis supported. 2) Each endogenous LV has a R² Endogenous are LV that received structural arrows. You could think in regression terms. Y = b1*x1 + b2*x2 + b3*x3 Here, we will have a R² for Y regression. 3) Yes path coefficients from report = m...

Hi, The LV scores from SmartPLS are not simple mean of the indicators, they are weighted by the outer weights). Suggestion to compare regression in a simple way: - use just one indicator by LV - run the model in SmartPLS, for example: (x1, x2, x3 --> y) - Run regression analysis (x1, x2, x3 --> y) i...

Hi Esmat,

The common procedure is:

1 = basic
2 =
3 = intermediate
4 =
5 = advanced

The idea is that the indicator is ordinal, but the sum of many indicators are about interval (summated rating scale).

Best regards,
Bido

Hi Timo, Your model is equivalent to “canonical correlation”, and this is one of the reason that I do not use canonical correlation analysis! Even with so small multicollinearity, maybe some nonsignificant outer weights could be caused by it. Suggestion: - Run a principal component analysis to group...

Hi Hussain, The short answer = yes. The long answer = If you are using reflective indicators: 1) Convergent validity: Outer loading = PLS / Calculation results / Outer loadings AVE = PLS / Quality criteria / Overview 2) Discriminant validity: Item level --> Crossloading = PLS / Quality criteria / cr...

Hi Dorthe, Usually our focus is on latent variables and path coefficients. If you are using reflective indicators: They could be replaced by others. For this reason, you should think more in LV terms than indicators. If you are using formative indicators, they could not be replaced by others. And we...

Hi Hussain, 1) The Classical about AVE and CC: Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18, 39–50. 2) Newer: Hair, J. F., Ringle, C. M., & Sarstedt, M. (2011). PLS-SEM: indeed...

Hi, yes, they are the same. If you want to test: - run the one model in SmartPLS, for example: (x1, x2, x3 --> y) - report / PLS / calculation results / Latent variable scores - copy these scores to a spreadsheet / import them to SPSS - Run the regression analysis (structural model). - compare the b...

Hi,
usually this kind of message is caused by missing values or strings or simbols ($, %, NA, etc.) in the dataset.
Best regards,
Bido

Some comments "One particular concern, often overlooked in PLS papers, is the lack of explicit convergence between the outcomes of the factor-analysis and the final model. 1) Bido: He is not clear, maybe he is talking about run a confirmatory factor analysis before the structural model (two st...

Hi, 1) Sample size: 1.1)A priori = How big should my sample be? - Look for the latent variable (LV) with the bigger number of arrows that arrive (could be from structural model ou from the formative measurement model). Use this number as "number of predictors" - Download G*Power3 from (htt...

Hi,

No.

I did not find some suggestion, even with other technique.

If the samples are independent, how could we test relations between variables of each dataset?

Best regards,
Bido

Hi, As I said, if you want to compute VIF for formative indicators: - use these indicators as independent variables in a multiple regression in SPSS and compute VIF there. More detailed: 1) Open your dataset in SPSS 2) Analyze / Regression / Linear / 3) Use as dependent variable any variable (could ...

Hi, If you want to compute VIF for formative indicators: - use these indicators as independent variables in a multiple regression in SPSS and compute VIF there. If you want to compute VIF for the structural model: - run the model in SmartPLS (PLS algorithm) - report - copy “PLS / Calculation results...