Hi,
You might want to check out FSL’s PALM tool, which has a bit more sophisticated permutation framework, and allows for permutation in the context of non-orthogonal covariates.
cheers,
-MH
--
Michael Harms, Ph.D.
-----------------------------------------------------------
Conte Center for the Neuroscience of Mental Disorders
Washington University School of Medicine
Department of Psychiatry, Box 8134
660 South Euclid Ave.
Tel: 314-747-6173
St. Louis, MO 63110
Email: mha...@wustl.edu
From: <freesurfer-boun...@nmr.mgh.harvard.edu> on behalf of Ajay Kurani <dr.ajay.kur...@gmail.com>
Reply-To: Freesurfer support list <freesurfer@nmr.mgh.harvard.edu> Date: Thursday, August 25, 2016 at 4:13 PM To: Freesurfer support list <freesurfer@nmr.mgh.harvard.edu> Subject: Re: [Freesurfer] mri_glmfit-sim permutation testing running after 3 days! Hi Doug,
Thanks for the help! I think I figured out the issue based on your response.
2) I deleted the folder and restarted without background processes. The error became apparent. Of my covariates (2 fix factors and 3 quantitative), not all were orthogonal. In looking at the error more, it seems that i need to add the
--perm-force if I wanted the simulation to run, however the background processes were not aware of this error and kept polling as you mentioned.
This brings me to a new but related issue. From what I have read in other freesurfer posts, it is statistically incorrect to use --perm-force for non-orthogonal covariates (or continuous covariates). I am unsure how to proceed.
a) If I ran permutation testing (to overcome the issue of incorrect smoothness estimations from the gaussian distribution assumption), then I run into the issue of non-orthogonal covariates. Is there a way to orthogonalize the data in freesurfer, or a solution to this issue?
b) If orthogonalizing is difficult to implement, another option is running Qdec with the montecarlo simulation at a more conservative p value (p< 0.001). From your previous posts, the testing at this p value for 10mm seems to meet the 5% FPR. One question
is if the non-orthogonal data affects this analysis as well for this model?
Thanks,
Ajay
On Thu, Aug 25, 2016 at 12:18 PM, Ajay Kurani
<dr.ajay.kur...@gmail.com> wrote:
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