Dear experts,
I have a question about statistical analyses of DTI data.
I am comparing DTI parameters between two groups (controls and patients) and eventually I also want to look at the correlation between performance on neuropsychological tests and DTI parameters. This is my plan of action (after performing the basic DTI processing) after much thought:
A- Run the randomise tool to obtain t-statistics and p-values for voxel-wise comparison between the two groups, corrected for multiple comparisons,
B- Threshold the output at the desired p-value. I am choosing 0.05 and further dividing it by 4 to account for multiple analyses (4 DTI parameters: FA, MD, RD and L1).
C- Use the thresholded image to find tracks with significantly different values.
D- Get the mean value in each of the significant track (here I use only that part of the tract where significant differences were found, i.e. only the part of the tract that was included in the thresholded image and not the entire track).
E- Use the mean values found in D to investigate the correlation with NP test performance in the patient group.
F- Use regression to account for variables like age, sex and disease stage.
The point where I got stuck was if I should use only the tracts with significant difference for further analyses or all the tracts. And if I should just use the mean value in the entire tract from the skeletonized parametric image, or un-skeletonized mean value in the entire tract or the skeletonized value from the significantly different region of the tract? I see people doing all of these things but I am not convinced for all.
Thank you for your expert opinion and help.
Eyesha
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