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Hi Martin,

Thanks for your reply, it's good to know that the mass-univariate approach
is still appropriate here.

Since the aseg segmentations are volumetric, can I still use the
*mris_preproc* and *mri_surf2surf* functions? If so, would the mri_preproc
function look something like *mri_preproc --qdec-long
/path/to/asegstats2table.long.table --target fsaverage --hemi rh --meas
volume --out output_dir/rh.volume.mgh*

If not, and I need separate functions, would *mri_surf2surf* be replaced by
*mri_vol2surf*?




On Thu, Jun 27, 2024 at 4:51 AM Reuter, Martin,Ph.D. <
mreu...@mgh.harvard.edu> wrote:

> Hi Dan,
>
> You could do either one. I would recommend the mass univariate for
> multiple independent test with the same design.
>
> Best, Martin
>
> On 26. Jun 2024, at 17:20, Dan Levitas <djlevitas...@gmail.com> wrote:
>
>
> I recently performed an LME longitudinal mass-univariate (surface)
> analysis and am now trying to do something similar, but with subcortical
> (aseg) ROIs instead.
>
> I first created an aseg table with the following command:
>
>
>
>
>
> * asegstats2table \ --sd $subjects_dir \ --qdec-long
> /path/to/long.qdec.table.dat \ --segno 4 10 11 12 17 18 26 43 49 50 51 53
> 54 58 251 253 255 \ --stats aseg.stats \ --tablefile $output_file*
>
>
> The LME tutorial (
> https://surfer.nmr.mgh.harvard.edu/fswiki/LinearMixedEffectsModels)
> provides information and examples of both a univariate and mass-univariate
> approach. While univariate seems most appropriate in this case, the example
> details design matrix setup and testing of a single ROI (hippocampus),
> whereas I would like to assess several subcortical ROIs.
>
> Would I simply create a loop structure to set up design matrices for each
> ROI (both hemispheres) and test them individually, or can I perform a
> mass-univariate approach to assess all ROIs at once?
>
> Thanks,
>
> Dan
>
>
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