Hi, I have a question about Feat higher-level analysis design setup. I have
one group of subjects who completed two tasks (tasks A and B) along with a
questionnaire measure. I want to correlate the questionnaire scores with
activation for each task and then compare the two beta maps (to find
significant differences between correlations). I'd like to have a design
that does this simultaneously, instead of having to run an HLA for each task
and then another that compares the Cope outputs. After looking at the Feat
webpage I've come up with a potential design (combining the Paired Two-Group
Difference and Single-Group Average with Additional Covariate designs) that
I want to make sure is correct. I set up an EV for each subject's
individual mean. I also have one EV that has questionnaire scores in each
input corresponding to task A and the same questionnaire scores multiplied
by -1 in the inputs for task B. I would then set up one Cope with a 1 for
EV1 and zeros everywhere else to get at the comparison I want. I left all
the Group inputs set as 1 to signify that all subjects are from the same
group. Below is an example of the design,
Input Group EV1 EV2 EV3 EV4 EV5 EV6
subject 1 task A 1 5 1 0 0 0 0
subject 2 task A 1 3 0 1 0 0 0
subject 3 task A 1 7 0 0 1 0 0
subject 4 task A 1 2 0 0 0 1 0
subject 5 task A 1 8 0 0 0 0 1
subject 1 task B 1 -5 1 0 0 0 0
subject 2 task B 1 -3 0 1 0 0 0
subject 3 task B 1 -7 0 0 1 0 0
subject 4 task B 1 -2 0 0 0 1 0
subject 5 task B 1 -8 0 0 0 0 1
Is this design correct? Also, if I didn't want to model each individual
subject's mean separately would it be valid to have the same design as above
except one column of 1's instead of EVs 2 though 6 (this seems more similar
to doing two HLA's and comparing the output as a paired t-test)? Thanks for
your time,
Jeff
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