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 _______________________________________________ Freesurfer mailing list Freesurfer@nmr.mgh.harvard.edu https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer
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