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, rstei...@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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