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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