Hi Gang, thank you for your answer!

> That seems right.
Thanks!

> In this case, it makes sense if your model contains the interaction term between Group and outcome1.
That makes sense.
Do you know why it produces a result even without the interaction effect being in the model? Would you expect the result to be different?

> So, if I interpret what you want correctly, just do -gltCode outcome1 'outcome1 :' \
Thanks, then I'll just stick with that.

> -gltCode outcome1_over_time 'outcome1 : Time :' \
> -gltCode outcome1_G1_over_time 'Group: 1*Group1 outcome1 : Time :' \
> -gltCode outcome1_GroupDiff_over_time 'Group: 1*Group1 -1*Group2 outcome1 : Time :' \
> These three lines don't make sense to me. Could you explain what are you exactly looking for?

Basically, after checking the association between covariate and imaging overall, I was trying to find out if this association changes over time (1).
Then, if this is true when looking at only Group1 (2). And then, if the change is differently for both groups (3).
But I think it is not possible/ does not make sense to model all of this at once, as it would basically be a three step question:
1. Is there an association between imaging and Outcome1?
2. If yes, does this association get stronger or weaker over time?
3. If it changes, is the magnitude of change different between the groups?

=> But now that I read this, it doesn't sound like it makes a lot of sense to try to extract all this from one model. Also, our sample size is most likely to small for questions beyond Question 1, to be answered meaningfully. So I guess I'll stick to question 1...