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
>>>>
>>>>
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