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<p class=MsoNormal><span style='font-size:11.0pt;font-family:"Calibri","sans-serif";
color:#1F497D'>Dear all,</span><span style='color:black'><o:p></o:p></span></p>
<p class=MsoNormal><span style='font-size:11.0pt;font-family:"Calibri","sans-serif";
color:#1F497D'> </span><span style='color:black'><o:p></o:p></span></p>
<p class=MsoNormal><span style='font-size:11.0pt;font-family:"Calibri","sans-serif";
color:#1F497D'>Recently I worked with a statistical analysis method called
Linear Mixed Models (LMM). This is relatively new to me so I hope I would not
say something wrong but here is my suggestion.</span><span style='color:black'><o:p></o:p></span></p>
<p class=MsoNormal><span style='font-size:11.0pt;font-family:"Calibri","sans-serif";
color:#1F497D'> </span><span style='color:black'><o:p></o:p></span></p>
<p class=MsoNormal><span style='font-size:11.0pt;font-family:"Calibri","sans-serif";
color:#1F497D'>Why not including the subjects as a factor in the statistical
analysis? The problem is that the subjects at hand do not represent the entire
population of subjects. The nice thing is that this is exactly what LMM can
handle through the use of random effects. However I guess that the statistical
analysis will always reject the null hypothesis that the dependent variable is
the same for all subjects, leading to difficult interpretation of the results.
Anyway that might be a starting point to answer your question. Any comments ?</span><span
style='color:black'><o:p></o:p></span></p>
<p class=MsoNormal><span style='font-size:11.0pt;font-family:"Calibri","sans-serif";
color:#1F497D'> </span><span style='color:black'><o:p></o:p></span></p>
<p class=MsoNormal><span style='font-size:11.0pt;font-family:"Calibri","sans-serif";
color:#1F497D'>In the case LMM are not familiar to you:</span><span
style='color:black'><o:p></o:p></span></p>
<p class=MsoNormal><span style='font-size:11.0pt;font-family:"Calibri","sans-serif";
color:#1F497D'><a
href="http://faculty.chass.ncsu.edu/garson/PA765/multilevel.htm">http://faculty.chass.ncsu.edu/garson/PA765/multilevel.htm</a></span><span
style='color:black'><o:p></o:p></span></p>
<p class=MsoNormal><span style='font-size:11.0pt;font-family:"Calibri","sans-serif";
color:#1F497D'> </span><span style='color:black'><o:p></o:p></span></p>
<p class=MsoNormal><span style='font-size:11.0pt;font-family:"Calibri","sans-serif";
color:#1F497D'>Hoping this can help,</span><span style='color:black'><o:p></o:p></span></p>
<p class=MsoNormal><span style='font-size:11.0pt;font-family:"Calibri","sans-serif";
color:#1F497D'> </span><span style='color:black'><o:p></o:p></span></p>
<p class=MsoNormal><span style='font-size:11.0pt;font-family:"Calibri","sans-serif";
color:#1F497D'>best regards,</span><span style='color:black'><o:p></o:p></span></p>
<p class=MsoNormal><span style='font-size:11.0pt;font-family:"Calibri","sans-serif";
color:#1F497D'> </span><span style='color:black'><o:p></o:p></span></p>
<p class=MsoNormal><span style='font-size:11.0pt;font-family:"Calibri","sans-serif";
color:#1F497D'>Guillaume Chanel</span><span style='color:black'><o:p></o:p></span></p>
<p class=MsoNormal><span style='font-size:11.0pt;font-family:"Calibri","sans-serif";
color:#1F497D'><o:p> </o:p></span></p>
<p class=MsoNormal><span style='font-size:11.0pt;font-family:"Calibri","sans-serif";
color:#1F497D'><o:p> </o:p></span></p>
<div>
<div style='border:none;border-top:solid #B5C4DF 1.0pt;padding:3.0pt 0cm 0cm 0cm'>
<p class=MsoNormal><b><span style='font-size:10.0pt;font-family:"Tahoma","sans-serif"'>From:</span></b><span
style='font-size:10.0pt;font-family:"Tahoma","sans-serif"'>
eeglablist-bounces@sccn.ucsd.edu [mailto:eeglablist-bounces@sccn.ucsd.edu] <b>On
Behalf Of </b>Arnaud Delorme<br>
<b>Sent:</b> 11. marraskuuta 2009 23:10<br>
<b>To:</b> Robert Brown<br>
<b>Cc:</b> eeglablist<br>
<b>Subject:</b> Re: [Eeglablist] statistics in EEGLAB<o:p></o:p></span></p>
</div>
</div>
<p class=MsoNormal><o:p> </o:p></p>
<p class=MsoNormal>Dear Bob,<o:p></o:p></p>
<div>
<p class=MsoNormal><o:p> </o:p></p>
</div>
<div>
<p class=MsoNormal>thanks for the comments. I think you are using the statmode
option "trial" from the command line. This option is quite
experimental. It was implemented a while ago and is probably not forward
compatible with more recent changes. Also, the "statmode",
"trials" option (assuming it was working) should only be
used to plot a single subjects. The reason is based on the type of null
hypothesis.<o:p></o:p></p>
</div>
<div>
<p class=MsoNormal><o:p> </o:p></p>
</div>
<div>
<p class=MsoNormal>When testing with 'statmode', 'subject' for two conditions,
the NULL hypothesis is: given the subjects I have recorded and given that these
subjects are a good representation of the general population of all possible
subjects, there is no difference between the ERP/spectrum/ERSP/ITC between the
two experimental conditions in the general subject population. Using
parametric, permutation, or bootstrap statistics (and assumptions) you may
either accept or reject this hypothesis at a given confidence level.<o:p></o:p></p>
</div>
<div>
<div>
<p class=MsoNormal><o:p> </o:p></p>
</div>
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<div>
<p class=MsoNormal>When testing with 'statmode', 'trial' on a single subject
(still two conditions), the NULL hypothesis is : given the trials I have
recorded and given that these trials are a good representation of all the
population of trials for this subject, there is no difference between the
ERP/spectrum/ERSP/ITC between the two experimental conditions for this
subject. Again, using parametric, permutation, or bootstrap statistics
(and assumptions) you may either accept or reject this hypothesis at a given
confidence level.<o:p></o:p></p>
</div>
<div>
<div>
<p class=MsoNormal><o:p> </o:p></p>
</div>
<div>
<p class=MsoNormal>As you can see the two hypothesis are quite different. One
makes an inference about the population of subjects and the other one about the
population of trials.<o:p></o:p></p>
</div>
<div>
<p class=MsoNormal><o:p> </o:p></p>
</div>
<div>
<p class=MsoNormal>Now if you pool the trials from different subjects and
attempt to perform statistics, this is going to be more complex. The new
hypothesis would then be: given the trials I have recorded from my
subjects and given that these trials are a good representation of all the
population of trials from the general population of subjects, there is no
difference between the ERP/spectrum/ERSP/ITC between the two experimental
conditions in the general population of subjects. But the hypothesis is
relatively biased because I personally think that all the trials are <b>not</b>
a good representation of all the population of trials from the general
population of subjects. The trials are a good representation of all the trials
from all the subjects being presently recorded but not necessarily of the
general subject population. Therefore the real NULL hypothesis would be
: given the trials I have recorded from all of my subjects and given that
these trials are a good representation of all the population of trials from
these subjects, there is no difference between the ERP/spectrum/ERSP/ITC
between the two experimental conditions in the recorded subjects. As you see,
rejecting the NULL this is relatively limited as we care about the general
population of subjects and not the recorded subjects.<o:p></o:p></p>
</div>
<div>
<p class=MsoNormal><o:p> </o:p></p>
</div>
<div>
<p class=MsoNormal>If anybody has some better ideas (or Matlab function) of how
to handle the subject/trial problem (because it would be nice to include trials
in statistical analysis in order to make them more powerful), we will take
them.<o:p></o:p></p>
</div>
<div>
<p class=MsoNormal><o:p> </o:p></p>
</div>
<div>
<p class=MsoNormal>Best,<o:p></o:p></p>
</div>
<div>
<p class=MsoNormal><o:p> </o:p></p>
</div>
<div>
<p class=MsoNormal>Arno<o:p></o:p></p>
</div>
<div>
<p class=MsoNormal><o:p> </o:p></p>
</div>
<div>
<p class=MsoNormal>ps: we will remove the 'statmode', 'trial' option for now.<o:p></o:p></p>
</div>
<div>
<p class=MsoNormal>pps: for basic inferential statistics, you may also refer to
this book chapter <a href="http://sccn.ucsd.edu/~arno/mypapers/statistics.pdf">http://sccn.ucsd.edu/~arno/mypapers/statistics.pdf</a><o:p></o:p></p>
</div>
<div>
<p class=MsoNormal><o:p> </o:p></p>
</div>
</div>
<div>
<div>
<div>
<p class=MsoNormal>On Nov 11, 2009, at 12:29 AM, Robert Brown wrote:<o:p></o:p></p>
</div>
<p class=MsoNormal><br>
<br>
<o:p></o:p></p>
<p class=MsoNormal style='margin-bottom:12.0pt'>Dear Arno & others,<br>
<br>
this does not seem to be as simple as Arno suggested (but thanks),<br>
<br>
1. I have precomputed the values of these channels (with
"savetrials", "on")<br>
2. these channels all have data<br>
3. I can plot the data of the same channels when I use "statmode",
"subjects"<br>
4. I'm using EEGLAB v7.1.3.13b <br>
5. I now tried it with v7.1.7.18b and I still get the log of zero error (you
guys might be interested that in addition I now get, in case of permutations
and bootstrap, "??? Error using ==> reshape" in
statcond>surrogate at 438 and statcond at 301 and with this latest version
the reshape error even happens with the "statmode",
"subjects")<br>
<br>
thus any other suggestions of what could be happening with my single trial
analysis in study would be very much appreciated.<br>
<br>
thank you very much and take care,<br>
Bob<o:p></o:p></p>
<div>
<p class=MsoNormal>2009/11/11 Arnaud Delorme <<a href="mailto:arno@ucsd.edu"
target="_blank">arno@ucsd.edu</a>><o:p></o:p></p>
<p class=MsoNormal>Dear Bob,<br>
<br>
I think this might be because you are trying to plot ERSP of a channel that
contains only 0. This error was also arising in old versions of EEGLAB when
masking for significance.<br>
<br>
Hope this helps,<br>
<br>
Arno<o:p></o:p></p>
<div>
<div>
<p class=MsoNormal style='margin-bottom:12.0pt'><br>
<br>
On Nov 7, 2009, at 11:38 AM, Robert Brown wrote:<o:p></o:p></p>
</div>
</div>
<blockquote style='border:none;border-left:solid #CCCCCC 1.0pt;padding:0cm 0cm 0cm 6.0pt;
margin-left:4.8pt;margin-right:0cm'>
<div>
<div>
<p class=MsoNormal>Hi guys,<br>
<br>
I've been trying to get the study ersp analysis working on single trials but
I've not succeeded.<br>
<br>
in the function "std_readdata" I get the "Warning: Log of
zero." error, which is on the line ersp{c,g} = 20*log10(abs(ersp{c,g}));
meaning that the absolute value at some point is 0.<br>
(This leads to) further errors:<br>
<br>
??? Error using ==> set<br>
Bad value for axes property: 'CLim'<br>
Values must be increasing and non-NaN.<br>
<br>
Error in ==> caxis at 80<br>
set(ax,'CLim',arg);<br>
<br>
Error in ==> tftopo at 714<br>
caxis([g.limits(5:6)]);<br>
<br>
I've tried to fix it but I'm not clever enough. any help would be appreciated.<br>
<br>
thank you so much,,<o:p></o:p></p>
</div>
</div>
<p class=MsoNormal>Bob <ATT00001.txt><o:p></o:p></p>
</blockquote>
<p class=MsoNormal><o:p> </o:p></p>
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<p class=MsoNormal><o:p> </o:p></p>
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<p class=MsoNormal><o:p> </o:p></p>
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