Dear Dr Zalesky,

Thank you so much for the swift reply!!

I have implemented what you have previously suggested but I am still having some issues so I was wondering if I could pick your brain regarding these matters

Q1. In relation to the previous matter, to answer your question: Yes all of the subjects have repeated measures. I have removed the global mean and the column representing one of the sites and done an F-test with the contrast [0,0,1,0,0,...], as you have suggested but I am still having the "rank deficient" warning. I played around with the model and found out that as soon as I declare the repeated measures that's when the warning is shown, but I have no idea what I'm doing wrong or how to fix it. As I previously said, I have three groups (HC,SZ,MDD) with 2 conditions (DL,DW) with subjects from 4 different sites (Site 1-4). In this model I'm trying to see the effect of the site using the grouping, age and gender as covariates. I have uploaded my full design matrix for this model, so any feedback you could give me would be greatly appreciated.

Q2. In continuation of the matter above, in the same paradigm but in a different comparison, I'm still having the same issue of rank deficient warning when declaring the repeated measures. I'm trying to compute the group difference between two groups (e.g. SZ vs HC) using and F-test with the contrast [1,0,0,0,0...] with site 1-4, age and gender as covariates. I have uploaded the full design matrix for this model as well so if you could give it a look I would be very grateful. An additional question for this is: as I am using the sites 1-4 as covariates should I have columns for all 4 sites or can the information regarding site 1 be inferred from the other 3 sites even when used as covariates?

Q3. And a final theoretical question that I always have problems with: When making the design matrix sometimes 1,0  is used to differentiate between groups, conditions etc. and sometimes 1,-1 is used. What is the way to know, which pair of values to use, for example in the case of these two models, because it is not always obvious to me...

Thank you very much for your time and consideration.

Best Alexandra