Since this is longitudinal, I'm assuming that your contrast is actually something like contrast C = (INT2-INT1)-(CON2-CON1) where 1 and 2 the the time points. As you suggest, both (INT2-INT1) and (CON2-CON1) might both be less than 0, but if INT is less negative than CON, then C will be positive and everything is working as it should (ie, there is not a problem or discrepancy here). What is the (complete) test that you are trying to accomplish?
On 8/23/2022 3:10 PM, rstein03@student.ubc.ca wrote:
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Hello Freesurfer Team,
I recently ran analysis to compare change in cortical thickness between an Intervention and Control group longitudinally. The contrast is set up as INT-CON, and therefore I would interpret a positive change as the intervention having a greater increase in cortical thickness or less atrophy than the control group.
The cluster that survived the Monte-Carlo simulation showed a positive difference in the LH superior parietal region when running both an ‘abs’ and ‘pos’ simulation (these showed the same cluster.summary outputs). There was not a significant cluster when running the ‘neg’ simulation. When I compared the mean change in thickness between groups (cache.th13.abs.y.ocn.dat file), it showed that the control group experienced less atrophy than the intervention despite having a positive cluster output.
One possible solution I considered is accounting for baseline differences between groups when looking at mean change. Does glmfit control for baseline cortical thickness in the cluster analysis that is not accounted for in the mean change values from the cache.th13.abs.y.ocn.dat file? Is there another possible explanation for this discrepancy?
Thank you in advance,
Ryan S
Ryan G. Stein
MSc Student, Rehabilitation Sciences
Aging, Mobility, and Cognitive Health Lab Djavad Mowafaghian Centre for Brain Health University of British Columbia | Vancouver Campus | Musqueam Traditional Territory
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