Summary of the experiment:
We have 3 conditions and 2 measurements per condition (pre and post), in a crossover design with 21 subjects. I was able to perform individual-run analyses and pre vs. post contrasts for each condition. However, I am encountering difficulties setting up a group-level analysis with these repeated measures (there are 6 total observations per subject).
Has anyone faced this issue and managed to plan an acceptable configuration using the FEAT GUI/FSL that could help me?
I use nipype to set up the contrast, because of the bunch of columns. I prefer the old fsl wiki:
https://fsl.fmrib.ox.ac.uk/fsl/oldwiki/FEAT(2f)UserGuide.html#Group_Statistics
Tripled Two-Group Difference (“Tripled” T-Test) or Multi-Session & Multi-Subject (Repeated Measures - Three Level Analysis).
For posterity, here is the link in our new documentation: https://fsl.fmrib.ox.ac.uk/fsl/docs/statistics/glm.html#single-group-three-measurements-tripled-t-test
Hi! This can be tricky. Do you have a rough matrix or a description of what your outcome contrast would ideally look like? Then I might be able to point you the right direction.
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