Hello all,
Apologies that this is a well-worn topic, but I remain confused after an afternoon of reading the forum. I need some clarification regarding using randomise to look at un-paired two-group differences (Patients and Healthy Controls). Looking at group differences without covariates, I set up my model and contrasts as below:
Model:
GRP EV1 EV2
PT 1 1 0
HC 2 0 1
Contrast:
1 -1
-1 1
1 0
0 1
I got some reasonable findings.
Yet, when I went to add nuisance covariates (by adding EVs 3 and 4) I got the “non-separable EVs” error message. After reading through this forum, I changed my setup for the covariate analysis to look like below (change being group assignment, in bold):
GRP EV1 EV2 EV3 (score1 demeaned) EV4 (score 2 demeaned)
PT 1 1 0 4 0.5
HC 1 0 1 -2 -0.25
Contrasts:
1 -1 0 0
-1 1 0 0
1 0 0 0 (grp mean)
0 1 0 0 (grp mean)
I have three questions
1) It seems one (or both!) of these ways of setting it up is incorrect, since one declares two different groups and one does not. I am most interested, ultimately, in the more complex covariate part.
2) Is this somehow different than what I would do if I were using FEAT?
3) Is there a way I can throw in a third covariate (of interest) to this model to see how strongly it correlates with activation differences or with one group's activation? (Or do I need to do this in a separate analysis, as currently planned.)
Thank you for help!
Matt
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