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Hi Amande,
I'm afraid I still don't understand what you want to do,
What do you mean by " a correlation with B _given_ A " ?
Is it a partial correlation
" a correlation of the data with B accounting for the effects A " ?
or a multiple regression
"How much of the variance in the data can a prescribe to both A and B
together?"
I'm sure there will be a simple way of answering your question. The GLM is
amazingly flexible. I just can't see exactly what the question is yet..
wrt non-orthogonal EVs
If your EVs are not orthogonal, then any shared variance will be dished
out between them in a way which is not easily predictable a priori.
However, if you are comparing conditions, this shared variance is
accounted for in the statisitics, so you can still accurately answer the
question "Where is the response to A bigger than that to B?" for example.
Sorry I'm not more use
Tim
On Sun, 27 Jun 2004, Amande Pauls wrote:
> Hi,
>
> no, what I was wondering about is whether there is any way I can test
> whether there is a correlation with B (behavioural covariate) given A
> (task), e.g. by not making the EVs orthogonal. So really what I want to
> know is what it means if the two EVs are not orthogonal and whether this
> is in any way statistically meaningful. Such as activation in a certain
> area given RT on the task, or activation in a task given IQ or something.
>
> Amande
>
>
>
> Tim Behrens wrote:
>
> > ...
> >
> > "At which voxels does my signal contain variance which can be explained by
> > my RTs _but not_ by my task EV ?"
> >
> > sorry - this might be confusing.
> >
> > more accurate is
> >
> > "At which voxels does my signal contain variance which can be explained by
> > my RTs after accounting for variance explained by my task EV ?"
> >
> >
> >
> > -------------------------------------------------------------------------------
> > Tim Behrens
> > Centre for Functional MRI of the Brain
> > The John Radcliffe Hospital
> > Headley Way Oxford OX3 9DU
> > Oxford University
> > Work 01865 222782
> > Mobile 07980 884537
> > -------------------------------------------------------------------------------
> >
> > ---------- Forwarded message ----------
> > Date: Wed, 23 Jun 2004 16:16:33 +0100 (BST)
> > From: Tim Behrens <[log in to unmask]>
> > To: FSL - FMRIB's Software Library <[log in to unmask]>
> > Subject: Re: [FSL] higher level analyses - using additional (behavioural)
> > covariates
> >
> > Hi Amande - I'm not sure whether I've understood this right, but it sounds
> > like what you want is exactly the opposite of the previous scenario. That
> > is
> >
> > "At which voxels does my signal contain variance which can be explained by
> > my RTs _but not_ by my task EV ?"
> >
> > If this is the case, you want to run the orthoganisation the other way
> > round. That is, you want to orthoganalise the RTs wrt the task covariates.
> >
> > This will remove from the RT EV, any variance which could be explained by
> > the task.
> >
> > Hope this is what you want
> >
> > T
> >
> >
> >
> >
> >
> >
> > On Wed, 23 Jun 2004, Amande Pauls wrote:
> >
> >
> >>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]
> >>>>
> >>>
> >>>
> >>
> >>--
> >>--------------------------------------------------------------------
> >>Amande Pauls
> >>University Laboratory of Physiology, Oxford, UK
> >>mailto:[log in to unmask]
> >>
> >
> >
>
>
> --
> --------------------------------------------------------------------
> Amande Pauls
> University Laboratory of Physiology, Oxford, UK
> mailto:[log in to unmask]
>
--
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Tim Behrens
Centre for Functional MRI of the Brain
The John Radcliffe Hospital
Headley Way Oxford OX3 9DU
Oxford University
Work 01865 222782
Mobile 07980 884537
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