Hi,
we have two groups with a covariate of interest and want to test the group*cov interaction effect in FEAT.
As far as I can tell, there are two ways to do that in FSL:
1)
intercept GroupA-B covar group*covar
1 -1 -3 3
1 -1 -2 2
1 1 1 1
1 1 4 4
with the following interaction-testing contrast:
intercept GroupA-B covar group*covar F-test
contrast 0 0 0 1 x
which has the disadvantage that I can't model separate variances. So I could also do:
2)
groupA groupB covarA covarB
1 0 -3 0
1 0 -2 0
0 1 0 1
0 1 0 4
with the following contrast:
groupA groupB covarA covarB F-test
contrast1 0 0 -1 0 x
contrast2 0 0 0 1 x
However, we are not too sure about the F-test in 2). Maybe it should be just:
groupA groupB covarA covarB F-test
contrast1 0 0 -1 1 x
Which one is correctly testing for the group*covariate interaction effect?
And would you expect the 1) and 2) model results to differ and if so, which model would you prefer (and why)?
Thanks for your help,
Esther
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