Hi Iselin,
This can be done using permutation tests, although not yet in randomise. It is available in PALM though. You'd proceed as this:
1) Assemble a design matrix as usual for a 3-group comparison:
EV1: Control group, coded as 0 if not control, or 1 if control.
EV2: High-risk group, coded as 0 if not high-risk, 1 if high-risk.
EV3: Affected group, coded as 0 if not affected, 1 if affected.
EV4, etc: Additional nuisance variables as needed, e.g., age, sex, etc.
2) Define the contrasts also as a 3-group comparison. For instance:
C1: [1 -1 0 0 ...], for Con > HR
C2: [1 0 -1 0 ...], for Con > Aff
C3: [0 1 -1 0 ...], for HR > Aff
C4: [-1 1 0 0 ...], for Con < HR
C5: [-1 0 1 0 ...], for Con < Aff
C6: [0 -1 1 0 ...], for HR < Aff
3) Define a file with the exchangeability blocks, one such block per sibship. I assume all sibships are complete and have size (cardinality) = 2. If the subjects are entered in the design in pairs, the EB file would be something as:
1
1
2
2
3
3
4
4
... etc
4) Run PALM with the desired options, making sure to use the options "-eb <EB file>", "-within" and "-whole". Something as this:
palm -i 4d_copes.nii.gz -d design.mat -t design.con -eb design.grp -within -whole -n 2000 -corrcon -logp -o myresults [other options]
The way as the permutations are created for these cases is described in
this paper. Subjects will be permuted within sibship, then the sibships will be permuted as a whole.
Interestingly, this design isn't properly seeking either "within-pair" or "between-pair" effects. Yet, it will inform about group differences while respecting the family relationships.
Hope this helps!
All the best,
Anderson