yes, no need to load rvar or the first computations of betamat and
rvarmat, and you don't need beta = ...
On 3/21/13 6:34 PM, Laura M. Tully wrote:
So this instead?
y = load('contrast/cache.th13.abs.y.ocn.dat');
X = load('Xg.dat');
beta = inv(X'*X)*X'*y;
C = load('contrast/C.dat');
So this instead?
y = load('contrast/cache.th13.abs.**y.ocn.dat');
X = load('Xg.dat');
beta = inv(X'*X)*X'*y;
C = load('contrast/C.dat');
rvar = MRIread('rvar.mgh');
betamat = fast_vol2mat(beta);
rvarmat = fast_vol2mat(rvar);
[betamat rvarmat] = fast_glmfit(y,X);
rho
oh, sorry, you'll need to recompute rvarmat (don't load rvar or beta)
[betamat rvarmat] = fast_glmfit(y,X);
Make sure you have $FREESURFER_HOME/fsfast/toolbox in your matlab path
doug
On 03/21/2013 05:04 PM, Laura M. Tully wrote:
> Hi Doug,
>
> I gave that a try but got a matrix error - below
Hi Doug,
I gave that a try but got a matrix error - below is the command line and
error output from matlab, can you spot what I'm doing wrong? (I'm a matlab
newbie I'm afraid...)
y = load('contrast/cache.th13.abs.y.ocn.dat');
X = load('Xg.dat');
beta = inv(X'*X)*X'*y;
C = load('contrast/C.dat');
It does it across the whole brain (on a voxel-by-voxel basis) but it is
specific to the contrasts that you specify. You can run the same
commands on the cluster averaged data (xxx.y.ocn...). To do this, don't
load in the beta file. Instead
y = load('xxx.y.ocn...');
beta = inv(X'*X)*X'*y;
then p
On 03/21/2013 01:37 PM, Gabriel Gonzalez Escamilla wrote:
> Thanks Doug for your quick answer,
>
> Sorry for so late answer.
>
> One question about this, is about the fast_vol2mat, is this a
> function? if so, where can I get it?
$FREESURFER_HOME/fsfast/toolbox
>
> As the PCC is the R value, I'm
I had this exact question yesterday :-) The functions necessary to run it
are in $FREESURFER_HOME/matlab and $FREESURFER_HOME/fsfast/**toolbox
Just add the path to these directories in your matlab (file -> setpath) and
you can run the function from your matlab command window
*Doug -* I had a follo
Thanks Doug for your quick answer, Sorry for so late answer.One question about this, is about the fast_vol2mat, is this a function? if so, where can I get it?As the PCC is the R value, I'm guessing that I can just square at it, to obtain R2.When you asked me to divide the beta by
sqrt(rvar), is
Hi Gabriel, I've attached a matlab routine which will compute the PCC.
If you cd into the GLM dir, then
X = load('Xg.dat');
beta = MRIread('beta.mgh');
C = load('yourcontrast/C.dat');
rvar = MRIread('rvar.mgh');
betamat = fast_vol2mat(beta);
rvarmat = fast_vol2mat(rvar);
rhomat = fast_glm_pcc(
Dear Freesurfers I'm performing regression analyses including confounding variables, and I would like to know how to obtain the following information:A) The squre Rand B) The standarized beta coefficient of an independient variable; and the partial correlation with its p-valuesMany thanks in advanc
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