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 <djlevitas208@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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