Hi,
a quick question about randomise. I've noticed on teh web page it says:
"if you have "confound regressors", randomise needs those to be removed
before continuing. Therefore, unlike with FEAT, you need to specify these
as a separate design matrix and use the -x option when calling randomise;
randomise then regresses these out of the data before continuing. Note
that for this to make sense, your confounds and design of interest need to
be orthogonal. In fact, in general in randomise, your regressors should be
orthogonal to each other."
I do not have confound regressors, but I want to perform a multi-regressor
analysis, to look at the effects of regressor1, regressor2 and
regressor1-by-regressor2 interaction. Does the above mean that I CANT do
it in randomise?
Cheers
Mara
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