You would keep both Perform and Age in addition to adding Perform*Age. I would first use DODS to test for a difference between groups in the Perform*Age variable [0 0 0 0 0 0 1 -1]. If there are no differences, then use DOSS to test for an effect of Perform*Age [0 0 0 0 1].
On 02/26/2018 04:40 PM, Martin Juneja wrote:
Thanks much Dough for your reply.
So if I add another column Performance*Age (after removing the mean of each) in my fsgd file (and remove individual columns for Performance and age), could you please tell what will be the contrast matrix (after only Gender as a covariate) in that case i.e. for following fsgd:
Class Male Class Female Variables *Perform*Age* Input S1 Male 180 Input S2 Female 167
Thanks.
On Mon, Feb 26, 2018 at 2:31 PM, Douglas N Greve <greve@nmr.mgh.harvard.edu mailto:greve@nmr.mgh.harvard.edu> wrote:
On 02/24/2018 12:00 AM, Martin Juneja wrote: > Hi experts, > > I am not sure if this has already been addressed in FS discussion. > > If my fsgd file looks like following: > > Class Male > Class Female > Variables Performance Age > Input S1 Male 181 25 > Input S2 Female 167 23 > .... > .... > > I understand that the contrast matrix *[**0 0 1 -1 0 0]* represents > whether there is a difference between the group > (male/female)-performance slopesregressing out the effect of age. In > other words, this matrix calculates whether two slopes i.e. one for > males: thickness-performance slope and second for females: > thickness-performance slope - are significantly different after > regressing out the effect of age. > > My questions are following: > > (1) Is my above interpretation of contrast matrix*[**00 1 -1 0 > 0]* correct? Yes > (2) If my interpretation is correct, then I was wondering what will be > the contrast matrix if *I want to check whether there is **significant > effect of age on e.g. thickness-performance slopes after regressing > out the effect of gender.* And what will be the corresponding fsgd > file for that, any changes in that? This is an interaction between continuous variables, which can be a little tricky. You cannot do it with the model that you have. The typical way to do this is to create a third covariate which is the product of Performance*Age; you should remove the mean of Performance and Age before doing the product. > > Thanks. > > > _______________________________________________ > Freesurfer mailing list > Freesurfer@nmr.mgh.harvard.edu <mailto:Freesurfer@nmr.mgh.harvard.edu> > https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer <https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer> -- Douglas N. Greve, Ph.D. MGH-NMR Center greve@nmr.mgh.harvard.edu <mailto:greve@nmr.mgh.harvard.edu> Phone Number: 617-724-2358 <tel:617-724-2358> Fax: 617-726-7422 <tel:617-726-7422> Bugs: surfer.nmr.mgh.harvard.edu/fswiki/BugReporting <http://surfer.nmr.mgh.harvard.edu/fswiki/BugReporting> FileDrop: https://gate.nmr.mgh.harvard.edu/filedrop2 <https://gate.nmr.mgh.harvard.edu/filedrop2> www.nmr.mgh.harvard.edu/facility/filedrop/index.html <http://www.nmr.mgh.harvard.edu/facility/filedrop/index.html> Outgoing: ftp://surfer.nmr.mgh.harvard.edu/transfer/outgoing/flat/greve/ <ftp://surfer.nmr.mgh.harvard.edu/transfer/outgoing/flat/greve/> _______________________________________________ Freesurfer mailing list Freesurfer@nmr.mgh.harvard.edu <mailto:Freesurfer@nmr.mgh.harvard.edu> https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer <https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer> The information in this e-mail is intended only for the person to whom it is addressed. If you believe this e-mail was sent to you in error and the e-mail contains patient information, please contact the Partners Compliance HelpLine at http://www.partners.org/complianceline <http://www.partners.org/complianceline> . If the e-mail was sent to you in error but does not contain patient information, please contact the sender and properly dispose of the e-mail.
Freesurfer mailing list Freesurfer@nmr.mgh.harvard.edu https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer