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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 <http://www.sciencedirect.com/science/article/pii/S105381191500508X> 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 On 5 October 2016 at 17:23, Iselin Meluken <[log in to unmask]> wrote: > Dear Experts > > I want to compare fMRI activity between three groups consisting of twins. > I want to be able to account for both non-independence between and within > groups and unequal group size. We have performed fMRI using four paradigms > assessing different domains of emotional processing. > > The individual twins are grouped according to personal and co-twin history > of affective disorders: > 1) Control Group: Both twins have no personal history of affective > disorders. Both twins in a twin pair are in the same group. N=29. > 2) High Risk group: The healthy co-twins of twins with affective disorder. > Only one twin from a twin pair is eligible in this group. N=33. > 3) Affected Group: Twins with a personal history of affective disorder. > Either the affected twin form a pair discordant for affective disrders or > both twins from a twin pair concordant for affective disorders. N=63. > > Would randomise/permutation testing be the best method of comparing these > groups or would you recommend another approach? Is it possible to account > for non-independence in traditional FEAT group analysis? > > Looking forward to you response! > Best Regards > Iselin Meluken >