I agree. For example, if there are 3 subjects, then simple binomial probability can give no better a result than p <= 12.5%. However, in the case that each single-subject effect, across single trials, is significant (e.g., at the p < .001% level), a much stronger inference can be derived using reasonable subject distribution assumptions.<div>
<br></div><div>Scott<br><br><div class="gmail_quote">On Thu, Nov 12, 2009 at 4:03 AM, Robert Brown <span dir="ltr"><<a href="mailto:bobrobbrown@googlemail.com">bobrobbrown@googlemail.com</a>></span> wrote:<br><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex;">
Dear Arno and All,<br><br>thank you very much for your enlightening response. <br><br>maybe one idea: let's say that I only have 4 subjects. the statistics based on "subject means" would be unreliable and I would not get any results. however, it could be that in case of each single subject there is a significant difference based on trials in the same time window, which would actually be a strong evidence for differences between the conditions and which could be written as "in case of each single subject p < .05 (corrected)". I am sorry if this is not right, but I assume that there could be instances where the group statistics with 3-4 subjects would not show anything but the single trial statistics would. (good examples of important studies with so few subjects would be Tong & Engel, 2001 in Nature with 4 subjects fMRI and Resulaj et al., 2009 in Nature with 3 subjects behavior.). <br>
<br>to conclude: maybe the single trial statistics would work, if it a) would be calculated individually for each subject based on only this subjects single trials and then b) the (time-frequency) regions would be plotted, where all the subjects have significant differences based on their single trial analysis.<br>
<br>thank you for your attention and good luck,<div><div></div><div class="h5"><br>Bob<br><br><div class="gmail_quote">2009/11/11 Arnaud Delorme <span dir="ltr"><<a href="mailto:arno@ucsd.edu" target="_blank">arno@ucsd.edu</a>></span><br>
<blockquote class="gmail_quote" style="border-left:1px solid rgb(204, 204, 204);margin:0pt 0pt 0pt 0.8ex;padding-left:1ex">
<div>Dear Bob,<div><br></div><div>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.</div>
<div><br></div><div>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.</div>
<div><div><br></div></div><div>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.</div>
<div><div><br></div><div>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.</div><div><br></div><div>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.</div>
<div><br></div><div>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.</div>
<div><br></div><div>Best,</div><div><br></div><div>Arno</div><div><br></div><div>ps: we will remove the 'statmode', 'trial' option for now.</div><div>pps: for basic inferential statistics, you may also refer to this book chapter <a href="http://sccn.ucsd.edu/%7Earno/mypapers/statistics.pdf" target="_blank">http://sccn.ucsd.edu/~arno/mypapers/statistics.pdf</a></div>
<div><br></div></div><div><div><div>On Nov 11, 2009, at 12:29 AM, Robert Brown wrote:</div><br><blockquote type="cite">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<br> <br><div class="gmail_quote">2009/11/11 Arnaud Delorme <span dir="ltr"><<a href="mailto:arno@ucsd.edu" target="_blank">arno@ucsd.edu</a>></span><br>
<blockquote class="gmail_quote" style="border-left:1px solid rgb(204, 204, 204);margin:0pt 0pt 0pt 0.8ex;padding-left:1ex"> 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<div><div></div><div><br> <br> On Nov 7, 2009, at 11:38 AM, Robert Brown wrote:<br> <br> </div></div><blockquote class="gmail_quote" style="border-left:1px solid rgb(204, 204, 204);margin:0pt 0pt 0pt 0.8ex;padding-left:1ex">
<div><div></div><div> 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,,<br></div></div> Bob <ATT00001.txt><br>
</blockquote> <br> </blockquote></div><br></blockquote></div><br></div></div></blockquote></div><br>
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