Print

Print


Hi Steve,

Thanks: so I should use:

Group   EV1     EV2     EV3     EV4 (age)
1       1       0       0       0.25
1       1       0       0       0.25
1       0       1       0       -0.75
1       0       1       0       0.5
1       0       0       1       -0.5
1       0       0       1       0.25

Further, my model was simplified: my actual design contains 90 subjects
divided over three groups. That is why I tried to model variances separately
for each group.

Regards, Serge.




-----Original Message-----
From: Stephen Smith [mailto:[log in to unmask]]
Sent: Wednesday, January 28, 2004 1:29 PM
To: [log in to unmask]
Subject: Re: [FSL] covariates of no interest at higher level

hi - that's nearly right, but you don't actually have the means in the
final model! You are right that you will need to set the group memberships
all equal (in fact if you only have 2 members in each group you shouldn't
be modelling the variances separately in the different groups separately
anyway). The model you should use is the original one with it's 3 EVs and
then add on the demeaned age EV as a 4th EV.

Cheers, Steve.



On Mon, 26 Jan 2004, SARB Rombouts wrote:

> Hi Steve,
>
> Thanks for the reply.
> This is what I did first (without age as covariate):
>
> Group   EV1     EV2     EV3
> 1       1       0       0
> 1       1       0       0
> 2       0       1       0
> 2       0       1       0
> 3       0       0       1
> 3       0       0       1
>
> Contrasts:
> A-B = EV1-EV2 = 1 -1 0
> A-C = EV1-EV3 = 1 -1 0
> B-C = EV2-EV3 = 0 1 -1
>
> Unfortunately, this model does not allow me to include one extra covariate
> for age, since I have 3 groups, and each EV should contain non-zero values
> for one group only, the other values must be zero....
>
> So the best model with age as covariate I could think of, was to pretend
as
> if all subjects belong to 1 group:
>
> Group   EV1     EV2     EV3 (age demeaned)
> 1       1       1       0.25
> 1       1       1       0.25
> 1       -1      0       -0.75
> 1       -1      0       0.5
> 1       0       -1      -0.5
> 1       0       -1      0.25
>
> Contrasts:
> A-B = EV1 = 1 0 0
> A-C = EV2 = 0 1 0
> B-C = EV2-EV1 = -1 1 0
>
> Is this how I should do it, or is there a better way to include age as
> covariate in one model? I would prefer modelling three different groups
> instead of just one.
>
> Thanks again,
> Serge.
>
>
>
>
> -----Original Message-----
> From: FSL - FMRIB's Software Library [mailto:[log in to unmask]] On Behalf
> Of Stephen Smith
> Sent: Monday, January 26, 2004 6:24 AM
> To: [log in to unmask]
> Subject: Re: [FSL] covariates of no interest at higher level
>
> Hi Serge.
>
> Correlating with age in a separate analysis isn't too useful - doesn't
> really tell you anything about the main analysis. Just because the effect
> is under threshold doesn't mean there isn't some correlation with age.
>
> So I would do the analysis all in one model. I'm not quite sure how you
> modelled age in the all-in-one analysis. I am assuming that the main part
> of the model has one EV each for A, B and C, with unpaired t-tests carried
> out with contrasts between these EVs. I would have thought the first thing
> to try with the age confound is to just add one extra EV with all the ages
> in it (but it must then be demeaned before putting into the model). Is
> this what you tried?
>
> Cheers, Steve.
>
>
>
>
> On Fri, 23 Jan 2004, Rombouts, S.A.R.B. wrote:
>
> > Hi,
> >
> >
> >
> > In a higher level FEAT analysis, I have 3 groups (A, B, C) and used a
> > 3-sample t-test to test for differences between groups (A-B, A-C, B-C).
> >
> > Since age may be a confounding factor in each comparison, I additionally
> > correlated data across groups with age (that is A + B (one group) with
age
> > as EV, A+C with age, and B+C with age). This appeared not to be the
case.
> >
> >
> >
> > Alternatively, when I analyse the data in a different way, with all EVs
in
> > one analysis (that is, EVs testing for group differences, and one EV
> > representing all ages), many group differences I saw in the first
> analysis,
> > disappear.
> >
> >
> >
> > I am confused about the proper way to analyse my data: which of the two
> > results is correct? Is it enough to check whether a covariate
> significantly
> > explains group differences in a separate analysis, or must I include all
> EVs
> > (both those of interest and those of no interest) in one big analysis?
> >
> >
> >
> > Thanks,
> >
> > Serge.
> >
> >
> >
> >
>
>  Stephen M. Smith  DPhil
>  Associate Director, FMRIB and Analysis Research Coordinator
>
>  Oxford University Centre for Functional MRI of the Brain
>  John Radcliffe Hospital, Headington, Oxford OX3 9DU, UK
>  +44 (0) 1865 222726  (fax 222717)
>
>  [log in to unmask]  http://www.fmrib.ox.ac.uk/~steve
>

 Stephen M. Smith  DPhil
 Associate Director, FMRIB and Analysis Research Coordinator

 Oxford University Centre for Functional MRI of the Brain
 John Radcliffe Hospital, Headington, Oxford OX3 9DU, UK
 +44 (0) 1865 222726  (fax 222717)

 [log in to unmask]  http://www.fmrib.ox.ac.uk/~steve