Hi Doug,
I know I'm reviving an old question. It seems to me that the variance of the errors estimated the way you are proposing below (i.e. using the residuals provided by selxavg3-sess) is biased in the sense that the residuals are not whitened (i.e. they are not independent becasue there is a temporal correlation), and that I could make an incorrect inference because of that. Am I right? If so, could you perhaps suggest a way of correcting for that?
Thank you very much,
Pablo
The residuals are not saved by default, but you can tell selxavg3-sess to save them by adding the -svres flag. By variance I mean the temporal variance of the mean waveform of the residuals. The t that you want is given by:
t = ces/sqrt(rvar * C'*inv(X'*X)*C)
where ces is the average ces over the ROI, the rvar is the variance described above, X is the design matrix, and C is the contrast matrix. Both of these are in the X.mat matrix.
doug
Pablo Polosecki wrote:
Oh, thank you. I am a little bit lost now. Could you clarify a little bit more for me? Could you tell where the residuals are stored?
By variance of the residuals you mean variance across voxels in the ROI?
What is the efficiency of the contrast?
On Thu, Nov 11, 2010 at 12:15 PM, Douglas N Greve <greve@nmr.mgh.harvard.edu <mailto:greve@nmr.mgh.harvard.edu>> wrote:
That's actually not the right way to do it either. You need to get
the residuals for the ROI, average the residuals, compute the
variance of the average residual. Then divide this by the
efficiency for the contrast, then take the sqrt() of this number.
This is the standard error of the ces. Then compute the average
ces over the ROI. The t is then the average ces/standard error.
doug
Pablo Polosecki wrote:
Well, that is bad (beacuse there is a bug) and good (because
now it is known) at the same time.
I wanted to estimate a p-value for a group of voxels of
interest for a certain contrast in my analysis. Instead of
averaging the p values for these voxels, I thought it would
make more sense to calculate the average t statistic for the
voxels and then estimate the p-value for the group of voxels
myself using tcdf function in matlab. So, I guess I need the t
values for that, unless I can think of a workaround, which so
far I couldn't.
Best,
Pablo
On Thu, Nov 11, 2010 at 11:57 AM, Douglas N Greve
<greve@nmr.mgh.harvard.edu <mailto:greve@nmr.mgh.harvard.edu><mailto:greve@nmr.mgh.harvard.edu
<mailto:greve@nmr.mgh.harvard.edu>>> wrote:
Hi Pablo, you have found a bug in FSFAST in which the values in
the t.nii file are actually the sqrt of the p-values. I
have fixed
it in our code base and it will be in the next version. Do you
actually need the t-values?
thanks!
doug
Pablo Polosecki wrote:
I understand the X.mat contains the variable DOF which
tells
me the degrees of freedom for the analysis, right? In
my case
it is 5915. This is what I get when I load X.mat into a
structure named 'x':
x =
DoSynth: 0
UseFloat: 0
SynthSeed: -1
flac0: [1x1 struct]
runflac: [1x21 struct]
X: [6048x133 double]
DOF: 5915
rfm: [1x1 struct]
yrun_randn: []
RescaleFactor: 5.6510
ErrCovMtx: 0
acfseg: [1x1 struct]
acfsegmn: [6048x1 double]
nrho1segmn: 0.1456
W: [6048x6048 double]
On Thu, Nov 11, 2010 at 11:35 AM, Douglas N Greve
<greve@nmr.mgh.harvard.edu
<mailto:greve@nmr.mgh.harvard.edu>
<mailto:greve@nmr.mgh.harvard.edu
<mailto:greve@nmr.mgh.harvard.edu>><mailto:greve@nmr.mgh.harvard.edu
<mailto:greve@nmr.mgh.harvard.edu>
<mailto:greve@nmr.mgh.harvard.edu
<mailto:greve@nmr.mgh.harvard.edu>>>> wrote:
what is your dof?
Pablo Polosecki wrote:
Oh, sure. It is:
t.vol(test_voxel_number)
ans =
-0.6368
On Thu, Nov 11, 2010 at 10:25 AM, Douglas N Greve
<greve@nmr.mgh.harvard.edu
<mailto:greve@nmr.mgh.harvard.edu>
<mailto:greve@nmr.mgh.harvard.edu
<mailto:greve@nmr.mgh.harvard.edu>>
<mailto:greve@nmr.mgh.harvard.edu
<mailto:greve@nmr.mgh.harvard.edu>
<mailto:greve@nmr.mgh.harvard.edu
<mailto:greve@nmr.mgh.harvard.edu>>><mailto:greve@nmr.mgh.harvard.edu
<mailto:greve@nmr.mgh.harvard.edu>
<mailto:greve@nmr.mgh.harvard.edu
<mailto:greve@nmr.mgh.harvard.edu>>
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<mailto:greve@nmr.mgh.harvard.edu>
<mailto:greve@nmr.mgh.harvard.edu
<mailto:greve@nmr.mgh.harvard.edu>>>>> wrote:
sorry, I meant what is the actual value of
the t in
t.vol(test_voxel_number)?
Pablo Polosecki wrote:
Firstly, thank you for the quickyresponse.
t.vol is the t-volume, loaded from t.nii
using
the MRIread
function (i.e. t=MRIread('t.nii');).
test_voxel_number
is just
some voxel of the volume that I'm using as an
example
in this
sanity check (I set it to 4000 in the sample
code but it
could have been anything else). I'm using
-(abs(t.vol(test_voxel_number)
)) because that is how I think the p-value is
calculated from
the t-statistic is a 2 tailed test. (See for
instance the
matlab code of the built-in ttest.m function
where you
have p
= 2 * tcdf(-abs(tval), df) with df being the
degrees of
freedom.) Still if I used the
alternative you
sugggest,
without the minus sign, I get:
my_pval=-log10(2*tcdf((abs(t.vol(test_voxel_number))),
x.DOF))
my_pval =
-0.1690
While I still have the stored p-value of
stored_pval =
-0.4055
Thanks again!
On Thu, Nov 11, 2010 at 10:02 AM,
Douglas N Greve
<greve@nmr.mgh.harvard.edu
<mailto:greve@nmr.mgh.harvard.edu>
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<mailto:greve@nmr.mgh.harvard.edu>
<mailto:greve@nmr.mgh.harvard.edu
<mailto:greve@nmr.mgh.harvard.edu>>>>
<mailto:greve@nmr.mgh.harvard.edu
<mailto:greve@nmr.mgh.harvard.edu>
<mailto:greve@nmr.mgh.harvard.edu
<mailto:greve@nmr.mgh.harvard.edu>>
<mailto:greve@nmr.mgh.harvard.edu
<mailto:greve@nmr.mgh.harvard.edu>
<mailto:greve@nmr.mgh.harvard.edu
<mailto:greve@nmr.mgh.harvard.edu>>>
<mailto:greve@nmr.mgh.harvard.edu
<mailto:greve@nmr.mgh.harvard.edu>
<mailto:greve@nmr.mgh.harvard.edu
<mailto:greve@nmr.mgh.harvard.edu>>
<mailto:greve@nmr.mgh.harvard.edu
<mailto:greve@nmr.mgh.harvard.edu>
<mailto:greve@nmr.mgh.harvard.edu
<mailto:greve@nmr.mgh.harvard.edu>>>>>> wrote:
what is t.vol(test_voxel_number)? Why
do you use
-(abs(t.vol(test_voxel_number)))
instead of
+(abs(t.vol(test_voxel_number)))?
doug
Pablo Polosecki wrote:
Dear experts,
For different reasons I found
myself double
checking the
relationship between t-values in t.nii
and p-values
stored in
sig.nii. If I use the following
matlab code I
thought
that I
should get the values of my_pval and
stored_pval
to be the
same (except perhaps for the sign):
cd(fullfile(basedir,session,'bold',anal,contrast))
x=load('../X.mat')
t=MRIread('t.nii');
sig=MRIread('sig.nii');
test_voxel_number=4000;
my_pval=-log10(2*tcdf(-(abs(t.vol(test_voxel_number))),
x.DOF))
stored_pval=sig.vol(test_voxel_number)
However I get:
stored_pval =
-0.4055
my_pval =
0.2804
Am I doing something wrong here? My
FreeSurfer
version
is 4.5
Thank you!
-- Pablo Polosecki
Graduate Fellow
Laboratory of Neural Systems
The Rockefeller University
1230 York Avenue, Box 9
New York, NY 10065
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