Hello experts!
I’m running the FBA pipeline in a study in which I have 2 groups (controls and patients) across 2 sessions (one at the start of the menstrual cycle and another in the middle), however not all subjects completed both sessions.
I want to see if there is any change of the fixel metrics between sessions (both in controls and in patients) and, more importantly, if there is any change between patients and controls in each session (so, controls session 1 vs patients session 1 and controls session 2 vs patients session 2).
To do so, below there is an example of the design matrix that I built (in the header there is the reasoning for the columns) along with the contrast matrix:
Intercept | Control | Patient | Session 1 | Session 2
1 1 0 1 0
1 1 0 0 1
1 1 0 1 0
1 0 1 0 1
1 0 1 1 0
----------
Contrast matrix:
0 1 -1 0 0
0 0 0 1 -1
However, as I understand it correctly, this will only analyse patients vs controls and session 1 vs session 2. Is there a way of analysing if there is any difference in the fixel metrics between the following groups specifically:
- controls session 1 vs patients session 1
- controls session 2 vs patients session 2
- controls session 1 vs controls session 2
- patients session 1 vs patients session 2
If so, what would the contrast matrix be like and do I need to alter the design matrix as well?
Furthermore, regarding the design matrix above, how can I make it not rank deficient? I have tried other ways but they end up always being rank deficient. For instance:
1 1 1
1 1 -1
1 1 1
1 -1 -1
1 -1 1
Also, given the analysis I want to perform, do I need to have a column per subject in the design matrix to account for subject differences?
Thanks in advance!
Best,
Ana