I don't think it is possible to do as a mixed effect. You can do this with the standard GLM by using a per vertex regressor (--pvr thickness.mgh to mri_glmfit)
On 06/27/2018 12:12 PM, Mark Wagshul wrote:
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Dear Freesurfer experts,
We are interested in looking at the moderating effect of grey matter thickness on a non-imaging outcome measure. Thus, the model would be:
Outcome measure = Condition + GM thickness + Condition * GM thickness
- covariates.
where Condition is a categorical variable (1/2, for two conditions of the non-imaging measures). The Freesurfer GLM usually solves for the thickness as a function of some contrast, but is really just determining the voxel-wise statistical significant of a GLM, so should be doable even with the imaging variable on the RHS. Ideally, we would like to run this as a linear mixed model with subject as a random effect, and the condition as a repeated measure.
Is this possible to do with the current Freesurfer software, and if so, how would I implement it?
Thanks for any advice you can provide.
Mark
Mark Wagshul, PhD Associate Professor Gruss Magnetic Resonance Research Center Albert Einstein College of Medicine Bronx, NY 10461
Ph: 718-430-4011
FAX: 718-430-3399
Email: mark.wagshul@einstein.yu.edu mailto:mark.wagshul@einstein.yu.edu
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