[VoxBo] Question about multiple contrasts in a glm

[David January]

Hi Dan,

I do want a positive slope to the line plotting activation as a Y
against condition as an X.  The reason I specified B > Rest in my
initial email is because I wanted to rule out getting a good fit with
a contrast that had A < Rest, B = Rest, and C > Rest.  The 1*A, 1*B,
and 1*C contrast precludes that, right?  Or would you recommend that I
find a region where (1*A, 1*B, 1*C) > rest and then look for the
(-1*A, 0*B, 1*C) contrast is significant?  My problem with that is I
wanted to do a whole brain analysis to find regions that showed the
parametric effect--I just don't want to find regions where A elicits
less activation than Rest.

-David

On 10/19/07, Daniel Y Kimberg <kimberg at mail.med.upenn.edu> wrote:
> David January wrote:
> > Hello everyone,
> >
> > I'm trying to find a linear trend among conditions in my data.  The
> > glm I have designed can be abstracted to be of the following kind,
> > with the conditions as column headings and the contrast covariates I
> > have included in the glm as the numbers below the column headings:
> >
> > Rest CondA CondB CondC
> > 0          1           1          1
> > 0          -1           0         1
> > 0          .5          -1        .5
> >
> > This combination of covariates should allow me to detect any relation
> > among the conditions that I care about.
> >
> > My question is this: if I want to which regions are showing the
> > pattern C > B > A, what do I enter in voxelsurfer (or vbview) to find
> > this?  I want B > rest, so I don't think I should just generate a
> > parametric map for covariate 2 alone; I should do both 1 and 2, right?
> >  But is just giving each of them a weight of 1 (and giving the 3rd a 0
> > weight) the correct thing to do?  Is there a problem with having the
> > weights I enter not even out to 0 (the way I would if I were directly
> > comparing A and B, for example)?  Also, when I do a random effects
> > analysis, should I set the contrast to include both covs 1 and 2?
> > would that cause any problems?
>
> If I understand correctly, it sounds like you need the voxel/region to
> support C>B and B>A and B>rest.  I don't think there's a way to test
> all three hypotheses with a single statistical contrast.  For example,
> while your second covariate, in the context of the first, will be
> sensitive to an increasing ABC function, it will also do well any time
> the overall slope from A to C is positive, even if the true slope from
> A to B is negative.  However, if by "linear trend" you just mean that
> you want a positive slope for the trend line plotting condition
> against activation, then you should be fine.
>
> Restricting your contrast to where B>rest (or maybe ABC>rest?) is a
> separate issue.  Generally speaking you can't test conjuntions of
> hypotheses in a single t-test just by weighting more covariates.  If
> you need multiple things to be true, you probably need to carry out
> all the relevant contrasts and either look at the intersection or
> (perhaps more powerful) look at your contrasts of greatest interest in
> regions defined by the more trivial contrasts.  E.g., you might define
> an ROI using your first covariate, and then within that ROI look for
> B-A and C-B, and plot the overlap.
>
> I hope this helps a bit, I'm not sure I really understood what you're
> trying to test here.
>
> > Sorry to be asking such a question, but my understanding of the
> > semantics of the commands is limited.
>
> Little if any of this is specific to VoxBo, or to image analysis in
> general.  I find it helpful when I'm trying to sort out how to model
> something to use a stats package to see what different potential
> models are sensitive to.  I have a few small statistical
> demonstrations up on the VoxBo wiki, and I've actually started to work
> on one describing how to test for a parametric effect, but it's not
> really ready to be posted yet.
>
> dan
>


-- 
David January
Department of Psychology
University of Pennsylvania