I would like to statistically compare fMRI data for two conditions (within
a single subject/run) - the first condition corresponding to 84 fMRI
images, and the second to 168 images. In other words, one condition was
on for twice as long as the other. When setting up this analysis in FEAT,
I am inclined to treat the data as if they are nothing more than two
datasets with unequal Ns, and create EVs where each image in the first
condition is coded with a 1, and each image in the second is coded with a
.5. I can then contrast those two EVs, applying a weight of 1 to the
first EV, and -1 to the second. My questions: is this how you would
choose to set up such an analysis? If not, how would you do it? Are
there any other considerations in implementing this type of analysis above
and beyond what's inherent statistically in comparing data with unequal Ns
- either within the context of FEAT, or in general for fMRI data?
Thanks,
John Herrington
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