Thanks for your reply,

I have a follow up on my first question - if however I was not looking for
a main effect of gender, but for the main effect of something else (e.g.
diagnosis), will it then be ok to include the unbalanced group (i.e.
A-male), to control for gender?

Thanks!

Regards
Yann

On 7 July 2017 at 18:34, <freesurfer-requ...@nmr.mgh.harvard.edu> wrote:

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> On 7/7/17 1:58 PM, Yann Ying Chye wrote:
> > Dear FreeSurfer mailing list,
> >
> > I've got two questions regarding the freesurfer GLM analysis.
> >
> > 1. I am trying to run mri_glmfit on the cortical thickness of a
> > dataset that has a few interacting factors of unequal levels.
> > For example, my dataset may have groups A, B, C, and D. Within the
> > groups, subjects are further divided by gender - male and female.
> > However, group A only has males, such that the classes in my FSGD file
> > = A-male, B-male, B-female, C-male, C-female, D-male, and D-female.
> > Will this design be a problem? Will it be statistically sound?
> > Additionally if I was looking for an effect of gender, how would I
> > weigh my contrast? I was thinking 0.25 0.25 -0.33 0.25 -0.33 0.25
> > -0.33. Would that be valid?
> I think I would lean against including A-male. Otherwise, what is the
> null hypothesis? Without A-male, it would be that males and females
> differ when regeressing out the effect of group, but you can't say that
> if you include A-male. Eg, if there were no difference between A-male
> and A-female but A tended to be larger than the other groups, then
> including A-male and not A-female would create a confound making males
> look bigger than females.
> > 2. Does mri_glmfit have a limit to the number of subjects it can run
> > with? If I have say upwards of a few thousand subjects, will this be
> > possible to run/how long would that take?
> I don't think it has a limit.
> >
> > Thanks for your help!
> >
> > Regards
> > Yann
> >
> >
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> End of Freesurfer Digest, Vol 161, Issue 17
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