Thanks Doug for your quick answer, <br /><br />Sorry for so late answer.<br /><br />One question about this, is about the fast_vol2mat, is this a function? if so, where can I get it?<br /><br />As the PCC is the R value, I'm guessing that I can just square at it, to obtain R2.<br /><br /><span>When you asked me to divide the beta by
    sqrt(rvar)</span>, is there any place where I can find is this is the correct way to get the <span>standardized beta</span>?<br /><br />Best regards,<br />Gabriel<br /><br /><div style="font-family: 'Times New Roman'; font-size: 16px;"><br /><br /><span>El 14/03/13, <b class="name">Douglas Greve </b> &lt;greve@nmr.mgh.harvard.edu&gt; escribió:</span><blockquote cite="mid:5141CA76.5060606@nmr.mgh.harvard.edu" class="iwcQuote" style="border-left: 1px solid #00F; padding-left: 13px; margin-left: 0;" type="cite"><div class="mimepart text html"><span><p>
  
    <meta content="text/html; charset=ISO-8859-1" http-equiv="Content-Type" />
  
  </p><p>
    Hi Gabriel, I've attached a matlab routine which will compute the
    PCC. If you cd into the GLM dir, then<br />
    <br />
    X = load('Xg.dat');<br />
    beta = MRIread('beta.mgh');<br />
    C = load('yourcontrast/C.dat');<br />
    rvar = MRIread('rvar.mgh');<br />
    <br />
    betamat = fast_vol2mat(beta);<br />
    rvarmat = fast_vol2mat(rvar);<br />
    <br />
    rhomat = fast_glm_pcc(betamat,X,C,rvarmat);<br />
    <br />
    rho = beta;<br />
    rho.vol = fast_mat2vol(rhomat,rho.volsize);<br />
    MRIwrite(rho,'yourcontrast/pcc.mgh')<br />
    <br />
    The R2 should just be the square of the PCC, right?<br />
    <br />
    For the standardized beta, do you just divide the beta by
    sqrt(rvar)?<br />
    <br />
    doug<br />
    <br />
    <br />
    </p><div class="moz-cite-prefix">On 3/14/13 1:39 PM, Gabriel Gonzalez
      Escamilla wrote:<br />
    </div>
    <blockquote cite="mid:96be2fd65c9d37f9.5141d309@upo.es" type="cite">
      <div style="font-family: 'Times New Roman'; font-size: 16px;"><br />
        Dear Freesurfers <br />
        <br />
        I'm performing regression analyses including confounding
        variables, and I would like to know how to obtain the following
        information:<br />
        <br />
        A) The squre R<br />
        <br />
        and <br />
        <br />
        B) The standarized beta coefficient of an independient variable;
        and the partial correlation with its p-values<br />
        <br />
        <br />
        Many thanks in advanced,<br />
        Gabriel<br />
        <br />
      </div>
      <br />
      <fieldset class="mimeAttachmentHeader"></fieldset>
      <br />
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</div></blockquote></div><br />-- <br /><font size="3">--------------------------<br />PhD. student Gabriel González-Escamilla<br />Laboratory of Functional Neuroscience<br />Department of Physiology, Anatomy, and Cell Biology<br />University Pablo de Olavide<br />Ctra. de Utrera, Km.1<br />41013 - Seville<br />- Spain -<br /><br />Email: ggonesc@upo.es<br />http://www.upo.es/neuroaging/es/</font>