Dear all,
Even if this thread already dates back some time I would like to ask a follow-up question on the different ways of tackling repeated-measures designs in FSL’s PALM:
1) Would the following approach be valid if used in PALM and specifying exchangeability blocks per participant (i.e. shuffling only within data of the same participant but not across different participants)?
As an example, a design where I have 3 participants, for each of which I obtained data in the 4 conditions of my fixed factor.
design ANOVA_rm.mat
eb GROUP cond1 cond2 cond3 sub01 sub02 sub03
1 1 1 0 0 1 0 0
2 1 1 0 0 0 1 0
3 1 1 0 0 0 0 1
1 1 0 1 0 1 0 0
2 1 0 1 0 0 1 0
3 1 0 1 0 0 0 1
1 1 0 0 1 1 0 0
2 1 0 0 1 0 1 0
3 1 0 0 1 0 0 1
1 1 0 0 0 1 0 0
2 1 0 0 0 0 1 0
3 1 0 0 0 0 0 1
…
Contrasts ANOVA_rm.con
Title EV1 EV2 EV3 EV4 EV5 EV6
Cond1 1 0 0 0 0 0
Cond2 0 1 0 0 0 0
Cond3 0 0 1 0 0 0
Cond1>2 1 -1 0 0 0 0
Cond1>3 1 0 -1 0 0 0
…
palm -i group1234.nii -d ANOVA_rm.mat -t ANOVA_rm.con -f ANOVA_rm.fts -Cstat mass -T -C 3.1 -Cnpc 3.1 -npcmethod Fisher -npccon -corrcon -logp -fdr -zstat -o out/ANOVA_rm -eb.csv -within
2) Using exchangeability blocks to allow shuffling only within subjects controls for repeated measures here. Hence, would this approach be valid? Or will all differential contrasts (i.e. contrast 4 and 5 in this example) need to be assessed via the calculation of simple difference copes (fslmaths) and a simple t-test? What about the correction for multiple comparisons across all contrasts in that case?
3) Can the PALM input files consist of concatenated inter-subject correlation 3D maps (nifti format), one per participant pair (which would be used equivalently to ‘participant’) and condition?
I would be really grateful for your help!
Lucie
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