On Fri, 1 Mar 2019, 23:58 Greve, Douglas N.,Ph.D., <DGREVE@mgh.harvard.edu> wrote:

just deman after you do the square root

On 3/1/19 3:49 AM, Abhinav Yadav wrote:
        External Email - Use Caution

Hi Douglas,

Thanks. But I want to see the square root of the age because I am assuming that the brain feature (cortical thickness) is varying in a square fashion.

Do I have to put square root values? If yes then, how can I put negative square roots. Since we have to put demeaned values.

Best,

Abhinav

On Fri, 1 Mar 2019, 01:44 Greve, Douglas N.,Ph.D., <DGREVE@mgh.harvard.edu> wrote:

If you wanted to do a simple analysis looking at the effect of age in a
linear fashion, you'd have a deisgn matrix something like
1 agesubject1
1 agesubject2
...

ie, first column all ones, second column the ages of each subject.
If you think the change is quadratic, then you'd use

1 agesubject1^2
1 agesubject2^2
...

ie, first column all ones, second column the square of the ages of each
subject.

Then use a contrast [0 1] to test whether the 2nd column regressor is
diff than 0. (btw, you should demean your ages before squaring)

On 2/28/19 12:12 PM, Abhinav Yadav wrote:
>
>         External Email - Use Caution
>
> Hi Douglas,
>
> Thanks for your reply. I am not sure how to do this with design
> matrix. I am trying to get higher order fit. Basically I want to see
> that whether the cortical thickness varies in a quadratic fashion with
> the behaviour score.
>
> Are you are suggesting that I should put square root values of the
> behavioural scores in the design matrix? I am not sure if that is the
> right approach.
>
> Looking forward to hearing back from you.
>
> Abhinav
>
> On Wed, 20 Feb 2019, 04:12 Greve, Douglas N.,Ph.D.,
> <DGREVE@mgh.harvard.edu <mailto:DGREVE@mgh.harvard.edu>> wrote:
>
> It sounds like you will just need to create your own design matrix
> and
> then feed it into mri_glmfit with --X (and not include --fsgd)
>
>
> On 2/12/19 12:03 AM, Abhinav Yadav wrote:
> >
> >         External Email - Use Caution
> >
> > Hello,
> >
> > I am trying to do GLM analysis for cortical thickness with a
> > behavioral score. I wanted to explore square fit in the GLM.
> Basically
> > wanted to see weather the behaviour is related in a quadratic
> function
> > instead of linear one.
> >
> > Couldn't find any option for this is GLM fit.
> >
> > I was thinking of feeding a squareroot values of the behavioural
> > parameter in the GLM as an alternative. But not sure weather
> that will
> > work. Please any one can help me with this.
> >
> > Thanks,
> > Abhinav
> >
> > _______________________________________________
> > Freesurfer mailing list
> > Freesurfer@nmr.mgh.harvard.edu
> <mailto:Freesurfer@nmr.mgh.harvard.edu>
> > https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer
>
>
> _______________________________________________
> Freesurfer mailing list
> Freesurfer@nmr.mgh.harvard.edu <mailto:Freesurfer@nmr.mgh.harvard.edu>
> https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer
>
>
> _______________________________________________
> Freesurfer mailing list
> Freesurfer@nmr.mgh.harvard.edu
> https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer

_______________________________________________
Freesurfer mailing list
Freesurfer@nmr.mgh.harvard.edu
https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer
_______________________________________________
Freesurfer mailing list
Freesurfer@nmr.mgh.harvard.edu
https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer
_______________________________________________
Freesurfer mailing list
Freesurfer@nmr.mgh.harvard.edu
https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer