Lets say, for simplicity’s sake we have a study with 3 subjects and 3 within
subjects conditions. We made 3 contrasts (corresponding to our 3
conditions). Participants gave pain ratings during our study which we now
want to correlate with the signal in the 3 conditions/contrasts.
Before moving forward with the analyses, I wanted to run this by the group.
I was thinking of running a higher-level analysis with 9 COPE files as inputs
Input
1 Sub1COPE1
2 Sub2COPE1
3 Sub3COPE1
4 Sub1COPE2
5 Sub2COPE2
6 Sub3COPE2
7 Sub1COPE3
8 Sub2COPE3
9 Sub3COPE3
I would model the data as follows
Group EV1(condition1) EV2 (condition2) EV3 (condition3) EV4 (pain ratings)
1 1 0 0 3
1 1 0 0 4
1 1 0 0 7
1 0 1 0 4
1 0 1 0 6
1 0 1 0 9
1 0 0 1 7
1 0 0 1 5
1 0 0 1 10
Orthogonalize EV4 with 1, 2, and 3
Contrast for Positive correlation would be
0 0 0 1
Contrast for Negative correlation would be
0 0 0 -1
Is this correct? Should I instead model pain ratings per condition as
separate EV’s then combine them as a contrast? Should my EV’s instead model
a given participant? My main concern is in accounting for the fact that the
9 datasets are not independent.
Many Thanks
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