Thanks again Martin. tp1 is really my baseline and so I want to compare the
rate of change from baseline to tp2 and tp3. So, I think the 1st option would
not work.
If I do use the longitudinal 2 stage model and then mri_glmfit, I would have 2
stacked files (1 for each comparison) and also, inside each 'base template'
folder, I would have 2 files of the spc (again, 1 for each comparison). In that
case, I think the mri_glmfit gets complicated with the --y option and the fsgd
file.
Thanks
Koushik Govindarajan
________________________________
From: freesurfer-boun...@nmr.mgh.harvard.edu
[freesurfer-boun...@nmr.mgh.harvard.edu] on behalf of Martin Reuter
[mreu...@nmr.mgh.harvard.edu]
Sent: Wednesday, July 22, 2015 4:11 PM
To: freesurfer@nmr.mgh.harvard.edu
Subject: Re: [Freesurfer] FSGD file for mri_glmfit in longitudinal 2-stage
model {Disarmed}
Yes, I mean the base name, but not repeated (so only lilsted once per base), so
you cannot simply copy that column from the long qdec file.
The PC1 is the slope of the linear fit with respect to the first time point
(the SPC with respect to the value of the linear fit at the mid time point and
is therefore more robust). What you ask (testing if percent change from 1 to 2
is different from the percent change from 1 to 3 is equivalent to testing if
tp2 is identical to tp3, so simply subtract the two and test for difference
from zero, e.g. you could do a PC1 for 2 to 3 and make a one sample group mean
(OSGM) test with glmfit. Not sure if this is really what you want to test. If
you are interested in differences in the slopes in the first and second
interval, you could run a linear mixed effects model with a pieciewise linear
approach and node at tp2. Or (if you only have 3 time points and they are
equally spaced in time) you could manually compute t2-t1 and t3-t2 and then the
difference of that yielding: 2*t2-t1-t3, then test for difference from zero
(OSGM).
Cheers, Martin
On 07/22/2015 04:55 PM, Govindarajan, Koushik Athreya wrote:
Thanks for the detailed reply Martin. When you say “here we mean really
subjects, not time points, as there is only one SPC map per subject”, are you
referring to the base template name?
Also, as an extension to my previous question, if I have 3 timepoints (tp1, tp2
and tp3). Is it possible for me to compare is pc1 of tp1 vs tp2 is
significantly different from pc1 of tp1 vs tp3? If so, would it be a qdec thing
or mri_glmfit method?
Thanks again
Regards
Koushik Govindarajan
From:
freesurfer-boun...@nmr.mgh.harvard.edu<mailto:freesurfer-boun...@nmr.mgh.harvard.edu>
[mailto:freesurfer-boun...@nmr.mgh.harvard.edu] On Behalf Of Martin Reuter
Sent: Wednesday, July 22, 2015 3:44 PM
To: Freesurfer support list
Subject: Re: [Freesurfer] FSGD file for mri_glmfit in longitudinal 2-stage model
Hi Koushik,
the output of the long_mris_slopes will be (by default) in each subjects
base/template directory, so you would have to map things to, e.g. fsaverage and
stack +smooth everythibng before running mri_glmfit. You can also make use of
the long_mris_slope flags --stack-spc <out> and --qcache fsaverage to create
stacked outputs at different smoothing levels mapped to fsaverage.
For running mri_glmfit, you would specify this stacked file as the --y input.
That takes care of it (it will use the spc instead of e.g. thickness). The fsgd
file needs to have the same order of subjects as in the long.qdec table (here
we mean really subjects, not time points, as there is only one SPC map per
subject).
Generally the FSGD file specifies the order of subjects and other co-variates
(e.g. age, IQ, gender). You do not specify the Y (dependent variable) in there.
That is only passed on the command line.
Best, Martin
On 07/22/2015 04:00 PM, Govindarajan, Koushik Athreya wrote:
Dear Freesurfers,
I am trying to use the longitudinal 2-stage model to run a mri_glmfit
analysis. How do I specify my FSGD file so that I compared spc or pc1 maps
instead of the regular thickness maps? Also, it is my understanding that I do
not have to run mris_preproc and mri_surf2surf since those are part of
long_mris_slopes. Is that right?
Thanks
Koushik Govindarajan
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Research Affiliate
Computer Science and Artificial Intelligence Lab,
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Massachusetts Institute of Technology
A.A.Martinos Center for Biomedical Imaging
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