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Dear all,<br>
<br>
I agree with Chris's description below. It is important to note that
this is not bootstrap but permutation statistics. Bootstraping would be
a way to find better confidence interval for the t-value BEFORE
performing a parametric test on it (comparing it to a table).
Permutation statistics involve recomputing the distribution of t-values
using permutation of conditions (by the way, this does not have
necessarily to be a t-value and can be any distance measure between the
two distributions). This may also be generalized to more than two
conditions using ANOVA and reconstruvtion of the ANOVA distribution
using permutation of conditions. This is described with example page 19
in the following document:<br>
<br>
<font face="Arial,Helvetica">Delorme, A. (2005) Statistical methods. <i>Encyclopedia
of Medical Device and Instrumentation</i>, in press. <a
href="http://www.sccn.ucsd.edu/%7Earno/mypapers/statistics.pdf"
target="_blank">PDF link</a>.</font><br>
<br>
A custom way to compensate for multiple comparisons is also described
below:<br>
<br>
<font face="Arial,Helvetica">Tanji, K., Suzuki, F., Delorme, A.,
Shamoto, H., and Nakasato N. (2005) High-Frequency Gamma-Band Activity
in the Basal Temporal Cortex during Picture-Naming and Lexical-Decision
Tasks. <i>J Neuroscience</i>, 25, 3287-3293. <a
href="http://www.jneurosci.org/cgi/content/full/25/13/3287?maxtoshow=&HITS=10&hits=10&RESULTFORMAT=1&author1=delorme&andorexacttitle=and&andorexacttitleabs=and&andorexactfulltext=and&searchid=1112980421492_6553&stored_search=&FIRSTINDEX=0&sortspec=relevance&journalcode=jneuro"
target="_blank">Journal's link</a>.<br>
<br>
Hope this helps,<br>
<br>
Arno<br>
</font><br>
Christopher Summerfield wrote:
<blockquote
cite="midPine.GSO.4.58.0602221644540.22649@paradox.psych.columbia.edu"
type="cite">
<pre wrap="">dear wu xiang
I think the procedure is outlined quite clearly in the Burgess & Gruzelier
article Phil Grieve just sent you, but to explain step by step...
1) you have coherence estimates at p electrode pairs for s subjects in 2
conditions. This means that you can perform a t-test at each electrode.
If you have several estimates per pair, for example several time bins, or
perhaps even an entire time-frequency map, you may have several
t-estimates per pair. I will call these 'point estimate' statistics.
2) at each pair, take your subject-condition assignments and swap them
1000 (or more times), recomputing your t-values at every pair or at every
timepoint or whatever. This will give you a null distribution
corresponding to every point estimate stat.
3) you can then determine whether each point estimate falls within alpha
of its null distribution.
4) to correct for multiple comparisons (for example, imagine that you have
20 electrodes=190 pairings), rather than checking each point estimate
against its distribution, enter (for each permutation) the maximum
statistic across your entire search space. So, in our example, if the
maximum permuted value from permutation 1 comes from electrode 188, you
enter that value into the null distribtuion. on the 2nd permutation, the
max value might come from another electrode. You then check all your
electrodes against this distribution. This will provide an 'familywise
error' correction for multiple comparisons.
good luck
Chris
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</pre>
</blockquote>
<br>
<br>
<div class="moz-signature">-- <br>
<br>
<b><font face="Arial,Helvetica"><font size="+1">Arnaud Delorme, Ph.D.</font></font></b>
<br>
<font face="Arial,Helvetica"><font size="+1"><font color="#3333ff">Swartz
Center for Computational Neuroscience,</font> <font color="#3333ff">INC,
University of San Diego California</font></font></font>
<br>
La Jolla, CA92093-0961, USA
<p><font face="Arial,Helvetica"><b>Tel</b> :<i>(+1)-858-458-1927 ext 15</i></font>
<br>
<font face="Arial,Helvetica"><b>Fax</b> :<i>(+1)-858-458-1847</i></font>
<br>
<font face="Arial,Helvetica"><b>Web page</b>: <a
href="http://www.sccn.ucsd.edu/%7Earno">sccn.ucsd.edu/~arno</a></font>
<br>
<font face="Arial,Helvetica"><b>To think upon</b>:</font></p>
<blockquote><dt><font face="Arial,Helvetica"> We have met the enemy,
and he is us.
<font size="-5"><br>
<br>
</font></font></dt>
<dd><font face="Arial,Helvetica"><i>Walt Kelly</i></font></dd>
</blockquote>
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