Here's my design matrix
1.000 0.000 -0.960 0.000 -0.170 0.000 1.860 0.000 1.970
0.000 2.010 0.000 2.140 0.000;
1.000 0.000 0.170 0.000 0.290 0.000 -0.560 0.000 -0.400
0.000 0.110 0.000 -0.260 0.000;
1.000 0.000 -0.050 0.000 0.750 0.000 -0.700
Can you resend the design matrix?
On 07/26/2016 11:46 AM, miracle ozzoude wrote:
> Hello Doug,
> Sure. Here are my new fsgd file and new contrast matrix ( matrix is
> the same as the old one).
> Best,
> Paul
> GroupDescriptorFile 1
> Title MOT
> Class Group1
> Class Group2
> Variables Age Educat
Hello Doug,
Sure. Here are my new fsgd file and new contrast matrix ( matrix is the
same as the old one).
Best,
Paul
GroupDescriptorFile 1
Title MOT
Class Group1
Class Group2
Variables Age Education Firstscore Secondscore Thirdscore Averagescore
Input 01053p/fsdir Group1 -0.96 -0.17 1.86 1.97 2.01
Can you send your new fsgd file and new design matrix?
On 7/24/16 6:06 PM, miracle ozzoude wrote:
Hello Doug or Bruce,
I demeaned and normalize like you suggested but I'm still getting the
same results. I created a new fsgd file using the demeaned and
normalized variables (n = (x-mean)/std(x)
Hello Doug or Bruce,
I demeaned and normalize like you suggested but I'm still getting the same
results. I created a new fsgd file using the demeaned and normalized
variables (n = (x-mean)/std(x). Any reason why? Thank you very much.
Paul
On Fri, Jul 22, 2016 at 6:43 PM, Douglas N Greve
wrote:
>
list
Subject: Re: [Freesurfer] mri_glmfit problem/2 group 6 covariates
Try demeaning and normalizing your continuous covariates in the FSGD file.
On 07/22/2016 06:17 PM, miracle ozzoude wrote:
>
> Hello doug,
>
> while running the mir_glmfit problem, i encountered this problem “
>
>
Try demeaning and normalizing your continuous covariates in the FSGD file.
On 07/22/2016 06:17 PM, miracle ozzoude wrote:
>
> Hello doug,
>
> while running the mir_glmfit problem, i encountered this problem “
>
> INFO: DeMeanFlag keyword not found, DeMeaning will NOT be done.
>
> Continuous Variab
Hello doug,
while running the mir_glmfit problem, i encountered this problem “
INFO: DeMeanFlag keyword not found, DeMeaning will NOT be done.
Continuous Variable Means (all subjects)
0 Age 39.9375 17.3312
1 Education 15.5625 1.99902
2 Firstscore 1.03375 0.341785
3 Secondscore 1.03906 0.3706
That means that you need to add something like
--surface fsaverage lh
the above assumes that you used the left hemi of fsaverage
On 09/05/2014 02:56 AM, Minjeong Wang wrote:
>
> Dear all,
>
> i have some problem with mri_glmfit.
>
> The error message is "you must use '--surface subject hemi'
Dear all,
i have some problem with mri_glmfit.
The error message is "you must use '--surface subject hemi' with surface
data"
What do I do for solving this problem??
Help me.. :(
M.J.
-
mri_glmfit \
--glmdir lh.cdr.glmdir \
--y lh.cdr.thickness.10.mgh \
why do you have all those back slashes? The command looks right, so try
removing them.
On 3/2/12 3:44 AM, Charlotte Bernard wrote:
Dear Freesurfer users,
I have tried to run mri-glmfit but I have obtained the error message:
ERROR: Option --y unknown
I don't understand why!
I have run that co
...@nmr.mgh.harvard.edu] On Behalf Of Charlotte Bernard
[chak...@live.fr]
Sent: Friday, March 02, 2012 2:44 AM
To: freesurfer
Subject: [Freesurfer] mri_glmfit problem with y option
Dear Freesurfer users,
I have tried to run mri-glmfit but I have obtained the error message: ERROR:
Option --y unknown
I don&#
Dear Freesurfer users,
I have tried to run mri-glmfit but I have obtained the error message: ERROR:
Option --y unknown
I don't understand why!
I have run that command line:
mri_glmfit \ --y lh.test.thickness.10.mgh \ --fsgd test.fsgd dods\ --C
group.diff.mtx \ --surf fsaverage lh \ --cortex \
in
Cc: freesurfer@nmr.mgh.harvard.edu
Subject:Re: [Freesurfer] mri_glmfit problem
The problem is that there is a strong correlation in the two continuous
variables due to their large non-zero means. The knee-jerk reaction is
to simply demean the variables which is sometimes the right thing
The problem is that there is a strong correlation in the two continuous
variables due to their large non-zero means. The knee-jerk reaction is
to simply demean the variables which is sometimes the right thing to do
and sometimes not. In this case, I think it is ok because you are using
DOSS.
Hi,
I am analysing structural data with mri_glmfit. After pre-processing I have
first used one group variable (gender) with one covariate age. I had no problem
processing the data and visualising it in tksurfer.
I then tried to add another covariate (measure of immediate recall). So I had
in t
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