Hello,
The design given in
https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/GLM#Two_Groups_with_continuous_covariate_interaction
Is a good place to start ( adding age,sex,smoking as extra EVs )
Although please note the important caveat in the wiki that group differences are extremely different to interpret in the presence of a significant interaction ( this also applies if you wish to test for interactions between age/sex and behaviour ). It will probably be necessary to use multiple designs - as the wiki says: if no interaction is found ( e.g. between group and behaviour ) then you can use the simpler model from https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/GLM#Two-Group_Difference_Adjusted_for_Covariate to test for group difference and behavioural correlation.
Hope this helps,
Kind Regards
Matthew
--------------------------------
Dr Matthew Webster
FMRIB Centre
John Radcliffe Hospital
University of Oxford
> On 27 Aug 2018, at 20:02, Zoe Guttman <[log in to unmask]> wrote:
>
> Hello,
>
> I'm trying to set up a model to determine whether resting-state functional connectivity is related to a behavioral measure (continuous, measure of loss aversion), is different between groups (patient and control), and the interaction effect of the behavioral measure and group. I also want to covary for age, sex, and smoking status, and I suspect there is an interaction between both age and sex with the behavioral measure. I'm confused as to whether I should do this all with one model or use separate models, and I'm new to FSL and not sure how to set up the EVs and contrasts.
>
> Thank you so much!
>
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