Hi there,
thanks for the quick reply.
I have another question about point (3). Say I don't want to factor out
the additional covariate, but want to see whether there are areas whose
variance reflects the additional covariate given the task. An example
would be some motor task and I want to 'rank' people according to RTs
I've got from them in some other task (or rather see whether activity in
this task somehow reflects their prior motor performance). Do I use RTs
from the other task as additional covariate and then don't make the EVs
orthogonal? Or do I have to set that up in the contrasts somehow, after
they have been orthogonalised?
What I would like to know is whether my additional covariate, of
interest or not, will correlate only with areas activated by the task,
or whether what I see could also reflect baseline activity in some
resting state network (like language areas etc).
Thanks again.
Amande
Tim Behrens wrote:
> Hi there
>
> On Tue, 22 Jun 2004, Amande Pauls wrote:
>
>
>>(1) Is it possible to control for an additional covariate that I am not
>>interested in but suspect to have an influence on the outcome of the
>>experiment (like measures of intelligence)? By modelling all of them as
>>an additional EV? Or by making it one per subject (like when allowing
>>for individual differences in variance)?
>
>
> Yep - you should use a single EV for each covariate of no interest (e.g.
> one EV for IQ, ine for age etc. etc. )
>
>
>>(2) If I want to know whether there is a negative correlation between my
>>additional covariate (modelled as a separate EV) and the data, do I need
>>to set the contrast to -1?
>>
>
>
> Yes - absolutely right.
>
>
>>(3) Having used an additional covariate (like the RT example in the
>>webpages) and using that precise contrast, what does the result mean?
>>I'm unclear on whether the brain area correlates both with RT and the
>>task itself, or whether the level activity in that area somehow reflects
>>RT, potentially independent of the task. Can I distinguish between those
>>two cases, or make sure that my contrast reflects 'correlation with
>>EV, given the task'?
>>
>
>
> It depends on the precise setup that you have chosen, but if you
> orthogonalise such that RT explains the maximum possible variance (i.e.
> orthogonalise all covariates of interest wrt RT) then the RT contrast
> represents all the variance in the signal which _might possibly_ be
> explained by RT. The copes of interest cannot then describe any variance
> in the signal which could be ascribed to RT.
>
> JHupw this is clear
>
> Tim
>
>
>
>
>
>>I hope this makes sense. Thanks for any help.
>>
>>Amande Pauls
>>
>>--------------------------------------------------------------------
>>Amande Pauls
>>University Laboratory of Physiology, Oxford, UK
>>mailto:[log in to unmask]
>>
>
>
--
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Amande Pauls
University Laboratory of Physiology, Oxford, UK
mailto:[log in to unmask]
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