Thanks again,
I have 3 subjects, and want to tests for effects using data collected across all 3 subjects. The multiple sessions for each subject have already been concatenated into a single BOLD folder (3 folders total: 1 for each subject). I have actually already performed the fixed effects analysis by concatenating all 3 subjects into a single bold folder and re-running the first level analysis. While that works, I now want to try to normalize the data for each subject to minimize the variability introduced by the contrast agent we use, and that would be easier to do by normalizing the outputs of the first level analysis. If I wanted to normalize per-subject and then combine them into a first level analysis, what would be the best way to do this?
My naive assumption would have been that using glmfit for this should be very similar to the repeated measures ANOVA example that is on the wiki (http://ftp.nmr.mgh.harvard.edu/fswiki/RepeatedMeasuresAnova). Rather than time points for each subject, I will have the beta from each condition for each subject. In both cases (multiple time points from a single subject and multiple conditions from a single subject/set of runs), the within-subject measurements are not independent. How is my situation different?
Cheers, Clark
On Nov 26, 2013, at 1:41 PM, Douglas N Greve greve@nmr.mgh.harvard.edu wrote:
Are the different input to glmfit different runs within a session or across sessions? Either way, for within subject analysis, can you put all of the runs into a single "bold" folder? Then it automatically does the FFX analysis across runs, which can include an F-test. The problem is that glmfit expects all the inputs to be independent, which conditions within a run will not be. doug
On 11/25/2013 01:35 PM, Clark Fisher wrote:
Thanks Doug,
I had forgotten that my roadblock was actually in isxconcat_sess, not mri_glmfit. This worked out great.
Following this up, how would you recommend calculating the fixed-effects significance of a complex (within subject) contrast with mri_glmfit? For simple contrasts, I have been calculating the contrast at the single subject level, then performing an osgm fixed-effects analysis on the output ces and cesvar volumes for each subject. However, I have some 2D F-contrasts that don't output ces volumes (naturally).
One possibility would be to concatenate the ces and cesvar from the omnibus contrasts of each subject, set up an appropriate fsgd (as in http://ftp.nmr.mgh.harvard.edu/fswiki/RepeatedMeasuresAnova) and then define the contrasts at the level of mri_glmfit with .mtx files. Would that be the way to go?
Thanks, Clark
-- Douglas N. Greve, Ph.D. MGH-NMR Center greve@nmr.mgh.harvard.edu Phone Number: 617-724-2358 Fax: 617-726-7422
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