Hi,
I tried the approach you have described earlier. I ran 3 separate 2nd levels to take 22 inputs (since we have 22 participants), which were cope1.nii.gz, cope3.nii.gz, or cope5.nii.gz files for the individual subjects. I had one contrast [1] and one f-test [C1]. After they finished running, I ran randomise under an identical GLM design:
randomise -i $SECONDLV/$COPE1.gfeat/cope1.feat/filtered_func_data -o $OUTPUT -d $DESIGN/design.mat -t $DESIGN/design.con -f $DESIGN/design.fts -1 -T
This gave me 6 files for each 2nd level:
fstat1
tfce_p_fstat1
tfce_corrp_fstat1
tstat1
tfce_p_tstat1
tfce_corrp_tstat1
All but one files have "normal" range of values, for the lack of a better word. However, tfce_corrp_fstat1, the only output that I am interested in at the moment, has all-0 values when checked with fslstats (or fslview). This feels pretty unnatural, since, again, the raw fstat and p-values for the fstat have normal ranges. I would have at least expected a distribution of very low (1-p) values.
So my quesiton is-- is this kind of behavior expected from randomise when it's working with f-stats?
Thank you,
Han-Gyol Yi
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