while writing the documentation of my model evaluation with SmartPLS I have some

**problems with the calculation and definition of SSO and SSE in SmartPLS 3.3.0**.

While looking at the formula for SSO in different papers I find that SSO should be the sum of squares of observations for each variable. When looking at the SmartPLS output I find that SSO is always calculated as:

*Sample Size * Number of Indicators*. (For example in the SmartPLS Book (German Version Page 188) SSO for ATTR is 1032,00 which equals

*3 * 344*.

So is it still true that SSO is the sum of squares of observations? Finally this leads to another problem, when calculating Q-Square. In my understanding Q-Square represents a comparison of the prediction errors of the model and the prediction errors of a simple estimation by the mean values? Where in the formula is the representation of the mean value estimation, when we calculate

*Q-Square = (1 - SSE/SSO)*?

Can someone please explain to me if I miss any intermediate steps or how SSO is exactly calculated so that it is exactly 1 for every data point of the latent variable (

*Sample Size * Number of Indicators*)?

I would be very grateful for every explanation.

Best regards

Fabian