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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