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<html><body style='font-size: 10pt'><div style="font-size: 12pt; font-family: Calibri,sans-serif;"><div>Hello again,</div><div><br></div><div>Just to clarify my last email: I'm referring to correlation between either single trial data within subject, or averaged ERPs across subjects, with a behavioral variable. Not linear regression across conditions as is already implemented in the ft_statfun_depsamplesregrT function.</div><div><br></div><div>Many thanks</div><div>Chris </div><div><br></div><div>Dr Christopher Brown</div><div>Research Associate</div><div><br></div><div>Sent from a mobile device, please excuse my brevity.</div><br><div id="htc_header">----- Reply message -----<br>From: "Christopher Brown" <cb802@cam.ac.uk><br>To: <fieldtrip@science.ru.nl><br>Subject: Cluster analysis on correlation statistics<br>Date: Sat, Dec 6, 2014 07:49</div></div><br>
<p>Dear all</p>
<p>I would like to use the cluster analysis functions in Fieldtrip on correlation statistics. I note there has been some discussion about this on this list in the past but I haven't come across the necessary ft_statfun_corr function to allow this analysis. It would be great if somebody has this code and could share it with me; otherwise, I will embark on writing it myself and sharing my results with everyone for feedback. Being new to Fieldtrip I would greatly appreciate any collaborative help with this. May I check my understanding on something before getting started: To allow for multiple comparisons correction using monte carlo for example, as part of a cluster analysis, I presume the output of the function must be t values rather than correlation coefficients? Any other hints as to how to write this are most welcome.</p>
<p>Kind regards</p>
<p>Chris</p>
<div>-- <br />
<pre><strong>Dr Christopher Brown</strong>
<em>Research Associate </em><em>| CamPain Group </em><em>| Division of Anaesthesia | School of Clinical Medicine | University of Cambridge</em> </pre>
<pre><br />Box 93 <br />Addenbrooke's Hospital <br />Hills Road <br />Cambridge CB2 0QQ <br /><br />01223 256 995</pre>
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