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Dear FSL-experts, I`m very surprised by the difference between two tbss analyses i ran. In fact, I forget to include the DTI images of one subject into a longitudinal analysis with 3 points in time and 2 groups. Thus I reran the analysis with altogether 13 subjects in each group and surprisingly, results differed extremly. Testing for a main effect of time and an interaction of groups with all 26 subjects included in the model all the skeleton shows up when looking at tfce-corrected fstat-images at p < .05 (> .95 in fsl-terminology). However, the same results look way more plausibel (two cluster at the expected location) when I only consider 25 subjects, that is to say with the subject that I initally forgot to incorporate in the analysis. I visually inspected the results of the preprocssing steps before subjecting data to tbss analysis as well as the results of the tbss analysis (e.g. the all_FA_skeletonized image, etc.), results look fine. I attached pictures of the design matrices and contrasts as well as the exchangeability block (EB) or to be precise ".grp" file/s. As can be seen from the design files, I only added one subject and of course adjusted the EB file accorindgly. The first 26 columns of my design matrix code subject factors, the last four columns the experimental group and control group at T1 and T2. The columns are respectively labeled in the design matrix. The last four columns look somewhat scrabbled which is due to the odering of subjects in the all_FA file which makes the membership of subjects to groups most likely only obvious to me. Randomise was used with the following commands: randomise -i all_FA_skeletonized.nii.gz -m -o ... -m mean_FA_skeleton_mask.nii.gz -d ... .mat -t ... .con -f ... .fts -e ... .grp --fonly -n 5000 --T2 -V.1 I would vey much appreciate any help on this as I´m a little bit desperate on how to explain this differences and on how to proceed. Thank you very much in advance. Raphael