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Ok. I see. However, I don't thing this was what I wanted to do. What I want to do is to control for age and gender differences between subjects, not within subjects (e.g. control for the fact that I have more younger than older participants, look at gender*time effects etc.). Sorry if I'm not being very clear. Alexander Michael Harms wrote: > You can't covary for gender in your repeated measure model, for the > reason that I explained. Try including a gender covariate and you'll > find that your design matrix will be rank deficient. As for age, it > would only be an option to consider if you want to use a different value > for age for each repeated visit of a subject, and even then I think > you'll get a poorly conditioned design matrix unless your age at the > repeated visits for a subject differed in an appreciable manner (where > "appreciable" would be relative to the variation in ages across > subjects). > > cheers, > -MH > > On Thu, 2011-05-12 at 19:44 +0200, Alexander Olsen wrote: > >> Hi Michael, >> Thank you so much for helping me. So that means that I should set up the >> design matrices without any covariates for age and gender? >> >> cheers, >> Alexander >> >> >> Michael Harms wrote: >> >>> Hi Alexander, >>> Given that you are modeling the mean of each subject using a repeated >>> measures design, that mean already incorporates that subject's age and >>> gender as part of its estimate. That is, if you added EVs for age >>> and/or gender, those EVs can be represented as a linear combination of >>> the columns modeling each subject's overall mean, and thus you would get >>> a degenerate design matrix. (This wouldn't strictly be true for age IF >>> the value you used for age differed across the repeated scans of a >>> subject, but unless your scans were spaced far apart temporally, you >>> still might get a poorly conditioned design matrix). >>> >>> cheers, >>> -MH >>> >>> On Thu, 2011-05-12 at 01:12 +0100, Alexander Olsen wrote: >>> >>> >>>> Dear FLS experts, >>>> >>>> I'm struggling a bit with setting up my analysis. What I would like to do is a repeated measures design with four timepoints, as in this example: >>>> >>>> http://www.fmrib.ox.ac.uk/fsl/feat5/detail.html#ANOVA1factor4levelsRepeatedMeasures >>>> >>>> However, I would also like to add age and gender as covariates in order to "remove" these effects. I hope anyone can help me, or direct me to an example which describes this. >>>> >>>> Thank you so much in advance. >>>> >>>> Alexander >>>> >>>>