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Have you looked at this page
https://secure-web.cisco.com/1HEsOws5HLh6urGfIzkrMbC_7g6t-p8fMP3vYoFDRvAWBsyZmdjmLZolBdJfAp6RF5d34864rZvnTvHUKt7jf7CxseHxsyQawYywC1Un3tELJ8hFiI-ukg1_Z0nHY4xuDoLLVHSXsHlAqFW1jps0N6tuwCDRTcbG9TbM-7GH2ywV6426IyNBD7IKjtAaQwrl-1eL0hpXPYP-cPjGca4vHX3HNxZjMG_nsWXVXsKd6tyJ09htrCWO2nM6lpkQfV1eW9jp4yIhykPG0KG7yzYTRDQ/https%3A%2F%2Fsurfer.nmr.mgh.harvard.edu%2Ffswiki%2FFsgdExamples ? Bascially I
think you will need number of classes = 2=M/F times N=#sights, then have
age and age^2 as your continuous regressors. With the FSGD, you have a
choice of a full interaction model (DODS=different offset different
slope) or have each continuous variable be its own column. What you are
describing would be a mixture of these things, so you would need to
create your own design in that case. Eg, you could have a column for
each class; the value=1 if that subject is in that class or 0 if not.
Then you'd have a column for age^2, then you would have two columns for
age, one would be the age if the subject is M otherwise 0, the other
would be age if the subject is F otherwise 0. You can pass the matrix to
mri_glmfit with the --X option (instead of using --fsgd).
On 9/4/2023 3:27 AM, #NGUYEN THUAN TINH# wrote:
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Dear Freesurfer experts,
I want to run a GLM to analyze the correlation between a continuous
variable Y and a morphometric measure (eg. Cortical thickness). I want
to control for some nuisance variables: sex, scan site, age, age
squared, age * sex interaction, head size.
1. How should I go about formulating the FSDG file?
2. What should my design matrix be if I am only interested in the
relationship between Y and the morphometric measure of interest
after controlling for the various nuisance variables?
Thank you so much for the help!
Yours,
Sophia
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