jamovi

Hi,
thanks, but maybe I'm not following your reasoning well. In general, in the general linear model, SS_model is not necessarily equal to SS_effects. It is not a bug.
If you have a balanced design for Genre and Volture, try removing the covariate Nbr and you'll see that SS_model=SS_effects. If Genre and Volture are not balanced or a covariate is in the model, SS_model is not necessarily equal to SS_effects.

Here is an example from Cohen and Cohen exercise example. Two continuous variables and their interaction (raw variables).
here the same in gamlj
You can see the results are identical (granted rounding).

You can also see the SS_model=5887, whereas SS_effects=2161+387+1136=3684
You can also see that SS_total=SS_model+SS_res=5887+22675=28561.

To finish up, here is an example with balanced data. In the first analysis, we just have two balanced factors, so SS_model=SS_effects
Now, adding a covariate change the sums and we get SS_model != SS_effects

The same is SPSS

My goodness, this is a part of the theory that I'd always completely overlooked. What a shame. Thank you so much for your help!

Hi,
So there is definitely some part of the theory that I overlooked, but for the record I found a computer with the older 2.6.1 still in place, so I can provide a proof that at some point 2.6.1 used to show SS_model = SS_effects.
Thanks again!
Arnaud

Current version and older version:

No problem, the important thing is that it is fine now. Thanks for the feedback