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 there any place where I can find is this is the correct way to get the standardized beta?
Best regards,
Gabriel
El 14/03/13, Douglas Greve <gr...@nmr.mgh.harvard.edu> escribió:
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(betamat,X,C,rvarmat);
rho = beta;
rho.vol = fast_mat2vol(rhomat,rho.volsize);
MRIwrite(rho,'yourcontrast/pcc.mgh')
The R2 should just be the square of the PCC, right?
For the standardized beta, do you just divide the beta by sqrt(rvar)?
doug
On 3/14/13 1:39 PM, Gabriel Gonzalez Escamilla wrote:
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 R
and
B) The standarized beta coefficient of an independient variable; and the partial correlation with its p-values
Many thanks in advanced,
Gabriel
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--
--------------------------
PhD. student Gabriel González-Escamilla
Laboratory of Functional Neuroscience
Department of Physiology, Anatomy, and Cell Biology
University Pablo de Olavide
Ctra. de Utrera, Km.1
41013 - Seville
- Spain -
Email: ggon...@upo.es
http://www.upo.es/neuroaging/es/
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