On 6/20/2022 3:42 PM, Julian Macoveanu wrote: > External Email - Use Caution > > Dear Freesurfers, > > I have a simple design with patients and controls and would like to > find regions showing group differences in cortical volume and > thickness. I also remove the effect of age, sex and ICV. Running the > GLM group analysis by the book I get a few clusters showing > significant differences in intercept. > > 1. I interpret this like patients have smaller “predicted” regional > volume at age 0, or at mean age of the group (if demeaned age > covariate) compared to controls. How can this finding be described in > a more clinically meaningful way? I'm not sure what you mean here. It seems like you have the interpretation correct. > > 2. Related to the above, how do I visualize what is going on in the > significant clusters? The extracted values from these clusters > (ocn.dat) show no group differences in volume when displaying the > group means in SPSS (using either age/sex/ICV adjusted or non-adjusted > values). Maybe I am misunderstanding something, how can there be > differences in intercept but no differences between group means? > (slopes not significantly different). How do I best describe and > visualize this group difference in a paper? You are probably not using the same model as mri_glmfit is using. You can try to feed the ocn.dat into the same mri_glmfit command with the --table option instead of --y. If you are going to do this, you will need to create a new table with the first column being the subject name and the first row being the clustername (eg, Cluster1, Cluster2, etc). The very first element (col=1 row=1) can be a dummy string (eg, "dummy") so that the table is complete.
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