Hi,

I tested for a difference between the groups on age slope using DODS and
there was a difference. Does this mean I cannot re-run the model using
DOSS? Please let me know if there is a way I can still test for the
difference in thickness between groups.
Thanks again,
Allie



On Mon, May 7, 2012 at 3:01 PM, Douglas N Greve
<gr...@nmr.mgh.harvard.edu>wrote:

> The right way to do it is to remove the column entirely. You can't do this
> inside of the FSGD unless you use DOSS. You can use DOSS if there is no
> difference between the groups in the age slope. In fact, it is a good idea
> to run this test first. So, create an FSGD with just the age. Create a
> contrast to test for a difference between the groups on age slope (and use
> DODS). If there are no differences, then re-run your original model using
> DOSS (you will need to change the contrast vector).
>
> doug
>
>
> On 05/07/2012 02:50 PM, Allie Rosen wrote:
>
>> Hi Doug,
>>
>> Is there a different number I can substitute into the fifth column so the
>> numbers are not all zeroes?
>>
>> Thank you,
>> Allie
>>
>>
>>
>> On Mon, May 7, 2012 at 12:39 PM, Allie Rosen <rosen.al...@gmail.com<mailto:
>> rosen.al...@gmail.com>**> wrote:
>>
>>    Hi Doug,
>>
>>    Thanks for the help. The fifth column is all zeroes because the
>>    covariate - length of disease - isn't applicable to control
>>    subjects. In the end, I want to test the difference in thickness
>>    between the two groups, regressing out the effect of both
>>    covariates (age and length of disease). I think this means the
>>    difference in intercepts between the two groups.
>>
>>    Thanks again,
>>    Allie
>>
>>
>>
>>    On Mon, May 7, 2012 at 12:29 PM, Douglas N Greve
>>    <gr...@nmr.mgh.harvard.edu 
>> <mailto:gr...@nmr.mgh.harvard.**edu<gr...@nmr.mgh.harvard.edu>>>
>> wrote:
>>
>>        Hi Allie, the 5th column of your design matrix is all 0s,
>>        which causes
>>        the ill conditioning. I don't think this design fits into our
>>        standard
>>        framework. You can still analyze and test, we'll just have to
>>        figure out
>>        exactly what needs to be done. In the end, what is it that you
>>        want to
>>        test? Just a difference in intercepts between the two groups?
>>        doug
>>
>>        On 05/07/2012 09:38 AM, Allie Rosen wrote:
>>        > Hello,
>>        >
>>        > I am analyzing cortical thickness in a patient and control
>>        group. I
>>        > have two covariates: age and length of disease. I am using
>>        the model from:
>>        >
>>        > 
>> http://surfer.nmr.mgh.harvard.**edu/fswiki/Fsgdf2G2V<http://surfer.nmr.mgh.harvard.edu/fswiki/Fsgdf2G2V>
>>        >
>>        > However, for the control group I put length of disease as 0
>>        in my FSGD
>>        > file. When I run the GLM, I get the following error message:
>>        >
>>        > matrix is ill-conditioned or badly scaled, condno = 1e+08
>>        >
>>        > Can you please tell me what I am doing wrong? Below is the
>>        required
>>        > information.
>>        >
>>        > 1. Your command line:
>>        >
>>        >     mri_glmfit --y lh.disease_length.thickness.**20.mgz --fsgd
>>        > fsgd_disease_length.txt dods --glmdir
>>        > lh.disease_length.thickness.**20.glmdir --surf fsaverage lh --C
>>        > groupdiff_length_disease.mat
>>        >
>>        >   2. The FSGD file
>>        >
>>        > GroupDescriptorFile 1
>>        > Title Anorexia vs Controls
>>        > Class Control plus blue
>>        > Class Patient circle green
>>        > Variables Age Disease_Length
>>        >
>>        > Input C07 Control 37 0
>>        > Input C28 Control 28 0
>>        > Input C39 Control 37 0
>>        > Input C54 Control 40 0
>>        > Input C57 Control 32 0
>>        > Input C10 Control 54 0
>>        > Input C33 Control 31 0
>>        > Input C29 Control 22 0
>>        > Input A01 Patient 39 20
>>        > Input A02 Patient 24 11
>>        > Input A03 Patient 35 15
>>        > Input A04 Patient 40 10
>>        > Input A05 Patient 35 20
>>        > Input A06 Patient 57 20
>>        > Input A07 Patient 31 16
>>        > Input A08 Patient 20 8
>>        >
>>        >   3. And the design matrix
>>        >
>>        > Design matrix ------------------
>>        >  1.000   0.000   37.000   0.000   0.000   0.000;
>>        >  1.000   0.000   28.000   0.000   0.000   0.000;
>>        >  1.000   0.000   37.000   0.000   0.000   0.000;
>>        >  1.000   0.000   40.000   0.000   0.000   0.000;
>>        >  1.000   0.000   32.000   0.000   0.000   0.000;
>>        >  1.000   0.000   54.000   0.000   0.000   0.000;
>>        >  1.000   0.000   31.000   0.000   0.000   0.000;
>>        >  1.000   0.000   22.000   0.000   0.000   0.000;
>>        >  0.000   1.000   0.000   39.000   0.000   20.000;
>>        >  0.000   1.000   0.000   24.000   0.000   11.000;
>>        >  0.000   1.000   0.000   35.000   0.000   15.000;
>>        >  0.000   1.000   0.000   40.000   0.000   10.000;
>>        >  0.000   1.000   0.000   35.000   0.000   20.000;
>>        >  0.000   1.000   0.000   57.000   0.000   20.000;
>>        >  0.000   1.000   0.000   31.000   0.000   16.000;
>>        >  0.000   1.000   0.000   20.000   0.000   8.000;
>>        > ------------------------------**--
>>        >
>>        > Thank you,
>>        > Allie
>>        >
>>        >
>>        >
>>        >
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>>        --
>>        Douglas N. Greve, Ph.D.
>>        MGH-NMR Center
>>        gr...@nmr.mgh.harvard.edu 
>> <mailto:gr...@nmr.mgh.harvard.**edu<gr...@nmr.mgh.harvard.edu>
>> >
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>> >
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>> >
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> --
> Douglas N. Greve, Ph.D.
> MGH-NMR Center
> gr...@nmr.mgh.harvard.edu
> Phone Number: 617-724-2358
> Fax: 617-726-7422
>
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