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.wags...@einstein.yu.edu <mailto:mark.wags...@einstein.yu.edu>
>
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