Hello,
I'm attempting to use TBSS and Randomise to run a very simple analysis where I look at which regions of white matter have FA values that correlate with a behavioral measure. I checked the archives and saw some similar questions but nothing corresponding to a straightforward, single group case like this. Moreover, I couldn't find much info on the Randomise and GLM user guide pages on how to run a simple correlation like this. I'd just like to check and see if I'm implementing this properly so that I can confidently interpret my results. Here are my design.mat and design.con files:
design.mat:
/NumWaves 2
/NumPoints 16
/Matrix
1 0.434234212
1 0.545979109
1 0.477247646
1 0.099429575
1 0.395724822
1 0.324461103
1 0.449161679
1 0.512661832
1 0.170029416
1 0.309619646
1 0.567401353
1 0.125277039
1 0.473249147
1 0.323318238
1 0.500022694
1 -0.375590874
design.con:
/NumWaves 2
/NumPoints 16
/Matrix
0 1
0 1
0 1
0 1
0 1
0 1
0 1
0 1
0 1
0 1
0 1
0 1
0 1
0 1
0 1
0 1
And here is the command I used to run the analysis. I used the -D option to demean the data since I entered raw values: randomise -i all_FA_skeletonised -o tbss -m mean_FA_skeleton_mask -d design.mat -t design.con -n 500 -D --T2
Currently when I run this command it does several rounds of the 500 permutations instead of just one, which doesn't seem correct. Any insight is greatly appreciated.
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