Re: [Freesurfer] Moderation analysis in Freesurfer

[Douglas N. Greve]

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:
>
> External Email - Use Caution
>
> 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 
>
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[Freesurfer] Moderation analysis in Freesurfer

[Mark Wagshul]

External Email - Use Caution

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

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This email message and any accompanying attachments may contain privileged 
information intended only for the named recipient(s). If you are not the 
intended recipient(s), you are hereby notified that the dissemination, 
distribution, and or copying of this message is strictly prohibited. If you 
receive this message in error, or are not the named recipient(s), please notify 
the sender at the email address above, delete this email from your computer, 
and destroy any copies in any form immediately.

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