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Hm... it seems that I may have reinvented the wheel (or perhaps
invented a cruder wheel before Eric and co provided this more
streamlined one).<br>
<br>
Eric, can indepsamplesregrT also compute nonparametric correlation
coefficients (eg Spearman)?<br>
<br>
Best,<br>
Tom<br>
<br>
<div class="moz-cite-prefix">On 12/8/2014 3:56 PM, Maris, E.G.G.
(Eric) wrote:<br>
</div>
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<div style="MARGIN: 0px"><font face="Times New Roman,serif"
size="3"><span style="FONT-SIZE: 12pt"><font color="#1f497d"
face="Calibri,sans-serif" size="2"><span
style="FONT-SIZE: 11pt">Hi Chris,</span></font></span></font></div>
<div style="MARGIN: 0px"><font face="Times New Roman,serif"
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<div style="MARGIN: 0px"><font face="Times New
Roman,serif" size="3"><span style="FONT-SIZE: 12pt"><font
face="Calibri,sans-serif"><span lang="en-US">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. </span></font><font
face="Calibri,sans-serif">Not linear regression
across conditions as is already implemented in the
ft_statfun_depsamplesregrT function.</font></span></font></div>
</div>
<div>
<div style="MARGIN: 0px"><font face="Times New
Roman,serif" size="3"><span style="FONT-SIZE: 12pt"></span></font> </div>
<div style="MARGIN: 0px"><font face="Times New
Roman,serif" size="3"><span style="FONT-SIZE: 12pt"><font
color="#1f497d" face="Calibri,sans-serif" size="2"><span
style="FONT-SIZE: 11pt" lang="en-US">For
correlating/regressing single trial data of a
single subject, you use the
ft_statfun_indepsamplesregrT (with the
units-of-observations being the trials, which
each correspond to one column of your design
matrix).
</span></font></span></font></div>
<div style="MARGIN: 0px"><font face="Times New
Roman,serif" size="3"><span style="FONT-SIZE: 12pt"><font
color="#1f497d" face="Calibri,sans-serif" size="2"><span
style="FONT-SIZE: 11pt" lang="en-US"></span></font></span></font> </div>
<div style="MARGIN: 0px"><font face="Times New
Roman,serif" size="3"><span style="FONT-SIZE: 12pt"><font
color="#1f497d" face="Calibri,sans-serif" size="2"><span
style="FONT-SIZE: 11pt" lang="en-US">For
correlating/regressing subject-averaged data of
a group of subjects, you also use the
ft_statfun_indepsamplesregrT (with the
units-of-observations being the subjects, which
each correspond to one column of your design
matrix). Note, in this case your behavioral
data (accuracy or RT) or also subject averages.</span></font></span></font></div>
<div style="MARGIN: 0px"><font face="Times New
Roman,serif" size="3"><span style="FONT-SIZE: 12pt"><font
color="#1f497d" face="Calibri,sans-serif" size="2"><span
style="FONT-SIZE: 11pt" lang="en-US"></span></font></span></font> </div>
<div style="MARGIN: 0px"><font face="Times New
Roman,serif" size="3"><span style="FONT-SIZE: 12pt"><font
color="#1f497d" face="Calibri,sans-serif" size="2"><span
style="FONT-SIZE: 11pt" lang="en-US">Best,</span></font></span></font></div>
<div style="MARGIN: 0px"><font face="Times New
Roman,serif" size="3"><span style="FONT-SIZE: 12pt"><font
color="#1f497d" face="Calibri,sans-serif" size="2"><span
style="FONT-SIZE: 11pt" lang="en-US"></span></font></span></font> </div>
<div style="MARGIN: 0px"><font face="Times New
Roman,serif" size="3"><span style="FONT-SIZE: 12pt"><font
color="#1f497d" face="Calibri,sans-serif" size="2"><span
style="FONT-SIZE: 11pt" lang="en-US">Eric Maris</span></font></span></font></div>
<div style="MARGIN: 0px"><font face="Times New
Roman,serif" size="3"><span style="FONT-SIZE: 12pt"><font
color="#1f497d" face="Calibri,sans-serif" size="2"><span
style="FONT-SIZE: 11pt" lang="en-US"></span></font></span></font> </div>
<div style="MARGIN: 0px"><font face="Times New
Roman,serif" size="3"><span style="FONT-SIZE: 12pt"><font
color="#1f497d" face="Calibri,sans-serif" size="2"><span
style="FONT-SIZE: 11pt" lang="en-US"></span></font></span></font> </div>
<div style="MARGIN: 0px"><font face="Times New
Roman,serif" size="3"><span style="FONT-SIZE: 12pt"><font
color="#1f497d" face="Calibri,sans-serif" size="2"><span
style="FONT-SIZE: 11pt" lang="en-US"></span></font></span></font> </div>
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<hr tabindex="-1">
<div id="divRpF665121" style="DIRECTION: ltr"><font
color="#000000" face="Tahoma" size="2"><b>Van:</b> Dr C A
Brown [<a class="moz-txt-link-abbreviated" href="mailto:cb802@cam.ac.uk">cb802@cam.ac.uk</a>]<br>
<b>Verzonden:</b> zaterdag 6 december 2014 12:33<br>
<b>Aan:</b> <a class="moz-txt-link-abbreviated" href="mailto:fieldtrip@science.ru.nl">fieldtrip@science.ru.nl</a><br>
<b>Onderwerp:</b> Re: [FieldTrip] Cluster analysis on
correlation statistics<br>
</font><br>
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<div>
<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" <a class="moz-txt-link-rfc2396E" href="mailto:cb802@cam.ac.uk"><cb802@cam.ac.uk></a><br>
To: <a class="moz-txt-link-rfc2396E" href="mailto:fieldtrip@science.ru.nl"><fieldtrip@science.ru.nl></a><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>
Box 93
Addenbrooke's Hospital
Hills Road
Cambridge CB2 0QQ
01223 256 995</pre>
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