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<div class=Section1>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>Dear Maren,<o:p></o:p></span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'><o:p> </o:p></span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'><o:p> </o:p></span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span lang=EN-US
style='font-size:12.0pt'>> I'm just trying out your excellent software, in
specific your extremely<o:p></o:p></span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> useful and well designed statistics functions.
Many thanks for this</span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> great and generous gift to the neuroscience
community!</span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> </span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> I would like to point you to an inconsistency I
seem to have found in</span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> the implementation of the statistics_montecarlo
function. When I</span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> compared the probabilities computed with
statistics_analytic and</span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> statistics_montecarlo for the depsamplesT test,
the probabilities</span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> determined via the randomization test turned out
to be too low by a</span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> factor of about 1/2, see code and Matlab output
below.</span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'><o:p> </o:p></span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'><o:p> </o:p></span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span lang=EN-US
style='font-size:12.0pt'>Most likely, there will be a bug in
statistics_montecarlo somewhere, but I do not think that your numerical demonstration
is evidence for such a bug. The following points are relevant in this respect:<o:p></o:p></span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span lang=EN-US
style='font-size:12.0pt'><o:p> </o:p></span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span lang=EN-US
style='font-size:12.0pt'>1. For a permutation test to be correct (in the sense
that it controls the false alarm rate), it is NOT required that it produces the
same p-value as the corresponding parametric test (i.e., using the same test
statistic and calculating the p-value under auxiliary assumption of normality).<o:p></o:p></span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span lang=EN-US
style='font-size:12.0pt'><o:p> </o:p></span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span lang=EN-US
style='font-size:12.0pt'>2. To show that there is a bug in the
statistics_montecarlo, you must show that its permutation p-values do not have
the properties they should have according to the theory behind permutation
tests (see, Maris and Oostenveld, in the most recent issue of the Journal of
Neuroscience Methods). For instance, you could do the following: <o:p></o:p></span></font></p>
<p class=MsoPlainText style='margin-left:36.0pt;text-indent:-18.0pt;mso-list:
l3 level1 lfo3'><![if !supportLists]><font size=3 face="Bookman Old Style"><span
lang=EN-US style='font-size:12.0pt'><span style='mso-list:Ignore'>1.<font
size=1 face="Times New Roman"><span style='font:7.0pt "Times New Roman"'>
</span></font></span></span></font><![endif]><span lang=EN-US>Take a test
statistic, e.g., the dependent samples t-statistic.<o:p></o:p></span></p>
<p class=MsoPlainText style='margin-left:36.0pt;text-indent:-18.0pt;mso-list:
l3 level1 lfo3'><![if !supportLists]><font size=3 face="Bookman Old Style"><span
lang=EN-US style='font-size:12.0pt'><span style='mso-list:Ignore'>2.<font
size=1 face="Times New Roman"><span style='font:7.0pt "Times New Roman"'>
</span></font></span></span></font><![endif]><span lang=EN-US>Generate N pairs
of observations from a bivariate distribution with identical marginal
distributions (this is the null hypothesis of a permutation test for a within-units
study).<o:p></o:p></span></p>
<p class=MsoPlainText style='margin-left:36.0pt;text-indent:-18.0pt;mso-list:
l3 level1 lfo3'><![if !supportLists]><font size=3 face="Bookman Old Style"><span
lang=EN-US style='font-size:12.0pt'><span style='mso-list:Ignore'>3.<font
size=1 face="Times New Roman"><span style='font:7.0pt "Times New Roman"'>
</span></font></span></span></font><![endif]><span lang=EN-US>Calculate the permutation
p-value under the permutation distribution, which is obtained by randomly permuting
the elements of the N pairs.<o:p></o:p></span></p>
<p class=MsoPlainText style='margin-left:36.0pt;text-indent:-18.0pt;mso-list:
l3 level1 lfo3'><![if !supportLists]><font size=3 face="Bookman Old Style"><span
lang=EN-US style='font-size:12.0pt'><span style='mso-list:Ignore'>4.<font
size=1 face="Times New Roman"><span style='font:7.0pt "Times New Roman"'>
</span></font></span></span></font><![endif]><span lang=EN-US>Repeat steps 2-3
a large number of times and calculate the proportion of times that it is less
than 0.05.<o:p></o:p></span></p>
<p class=MsoPlainText style='margin-left:36.0pt;text-indent:-18.0pt;mso-list:
l3 level1 lfo3'><![if !supportLists]><font size=3 face="Bookman Old Style"><span
lang=EN-US style='font-size:12.0pt'><span style='mso-list:Ignore'>5.<font
size=1 face="Times New Roman"><span style='font:7.0pt "Times New Roman"'>
</span></font></span></span></font><![endif]><span lang=EN-US>If the proportion
in 4. is significantly different from 0.05 (the nomical alpha-level) you have
shown that there is bug in statistics_montecarlo.<o:p></o:p></span></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span lang=EN-US
style='font-size:12.0pt'><o:p> </o:p></span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span lang=EN-US
style='font-size:12.0pt'>A simulation study of the type described here was
performed by Maris, Schoffelen, & Fries (2007, also in the Journal of
Neuroscience Methods) to show that a permutation test for coherence differences
controls the false alarm rate whereas the corresponding parametric test does
not.<o:p></o:p></span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span lang=EN-US
style='font-size:12.0pt'><o:p> </o:p></span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span lang=EN-US
style='font-size:12.0pt'><o:p> </o:p></span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span lang=EN-US
style='font-size:12.0pt'>Kind regards,<o:p></o:p></span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span lang=EN-US
style='font-size:12.0pt'> <o:p></o:p></span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span lang=EN-US
style='font-size:12.0pt'><o:p> </o:p></span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span lang=EN-US
style='font-size:12.0pt'>Eric Maris<o:p></o:p></span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span lang=EN-US
style='font-size:12.0pt'><o:p> </o:p></span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span lang=EN-US
style='font-size:12.0pt'>dr. Eric Maris<o:p></o:p></span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span lang=EN-US
style='font-size:12.0pt'>NICI/Biological Psychology and<o:p></o:p></span></font></p>
<p class=MsoPlainText><st1:place w:st="on"><st1:PlaceName w:st="on"><font
size=3 face="Bookman Old Style"><span lang=EN-US style='font-size:12.0pt'>F.C.</span></font></st1:PlaceName><span
lang=EN-US> <st1:PlaceName w:st="on">Donders</st1:PlaceName> <st1:PlaceType
w:st="on">Center</st1:PlaceType></span></st1:place><span lang=EN-US> for
Cognitive NeuroImaging<o:p></o:p></span></p>
<p class=MsoPlainText><st1:place w:st="on"><st1:PlaceType w:st="on"><font
size=3 face="Bookman Old Style"><span lang=EN-US style='font-size:12.0pt'>University</span></font></st1:PlaceType><span
lang=EN-US> of <st1:PlaceName w:st="on">Nijmegen</st1:PlaceName></span></st1:place><span
lang=EN-US><o:p></o:p></span></p>
<p class=MsoPlainText><st1:address w:st="on"><st1:Street w:st="on"><font
size=3 face="Bookman Old Style"><span lang=EN-US style='font-size:12.0pt'>P.O.
Box</span></font></st1:Street><span lang=EN-US> 9104</span></st1:address><span
lang=EN-US><o:p></o:p></span></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span lang=EN-US
style='font-size:12.0pt'>6500 HE Nijmegen<o:p></o:p></span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span lang=EN-US
style='font-size:12.0pt'>The <st1:country-region w:st="on"><st1:place w:st="on">Netherlands</st1:place></st1:country-region><o:p></o:p></span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span lang=EN-US
style='font-size:12.0pt'>T:+31 24 3612651 (NICI)<o:p></o:p></span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>T:+31 24 3610754 (FCDC)<o:p></o:p></span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>F:+31 24 3616066 (NICI)<o:p></o:p></span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>E: maris@nici.ru.nl<o:p></o:p></span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span lang=EN-US
style='font-size:12.0pt'>MSc Cognitive Neuroscience :www.ru.nl/master/cns/<o:p></o:p></span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span lang=EN-US
style='font-size:12.0pt'><o:p> </o:p></span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> -------------------------</span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> </span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> N = 50;</span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> M = 0.25;</span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> alpha = 0.05;</span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> tail = 0; % 'both'</span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> </span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> % construct a normally distributed difference
vector</span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> % with unit variance and mean M</span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> d = randn(1,N);</span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> d = d ./ sqrt(var(d,1,2));</span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> d = d -mean(d) + M;</span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> </span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> % compute a paired t-test</span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> [H,P,CI,stat] = ttest(d,0,alpha,tail)</span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> </span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> H =</span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> </span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> 0</span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> </span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> </span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> P =</span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> </span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> 0.0864</span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> </span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> </span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> CI =</span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> </span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> -0.0371
0.5371</span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> </span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> </span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> stat =</span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> </span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> tstat: 1.7500</span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> df: 49</span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> sd:
1.0102</span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> </span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> % generate two sample vectors with their
difference given by d</span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> x =randn(1,N);</span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> y = x + d;</span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> </span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> % generate the design matrix for testing with
fieldtrip</span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> design = [</span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> 1:N
1:N
% subject number</span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> repmat(1,[1 N]) repmat(2,[1
N]) % condition number</span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> ];</span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> </span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> cfg = [];</span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> cfg.statistic
= 'depsamplesT';</span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> cfg.method
= 'analytic';</span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> cfg.correctm
= 'no';</span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> cfg.alpha
= 0.05;</span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> cfg.tail
= 0;</span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> cfg.uvar
= 1;</span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> cfg.ivar
= 2;</span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> </span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> [stat_analytic, cfg] = statistics_analytic(cfg,[x
y],design)</span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> </span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> stat_analytic =</span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> </span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> stat:
-1.7500</span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> df:
49</span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> critval: [-2.0096 2.0096]</span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> prob:
0.0864</span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> mask: 0</span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> </span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> cfg.numrandomization = 5000;</span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> [stat_montecarlo, cfg] =
statistics_montecarlo(cfg,[x y],design)</span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> </span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> using "statfun_depsamplesT" for the
single-sample statistics</span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> constructing randomized design</span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> total number of
measurements = 100</span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> total number of
variables = 2</span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> number of independent variables = 1</span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> number of unit
variables = 1</span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> number of control
variables = 0</span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> number of within-block variables = 0</span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> repeated measurement in variable 1 over 50 levels</span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> number of repeated measurements in each level is
2 2 2 2 2 2 2 2 2 2 2 2</span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
2 2 2 2 2 2 2 2 2 2 2 2 2</span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> estimated time per randomization is 0 seconds</span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> not performing a correction for multiple
comparisons</span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> </span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> stat_montecarlo =</span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> </span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> prob: 0.0394</span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> mask: 1</span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> stat: -1.7500</span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> </span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> --------------------</span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> </span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> Maybe I'm missing something. But I think you should
replace</span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> </span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> stat.prob = min(prb_neg, prb_pos);</span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> by</span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> stat.prob = 2 *min(prb_neg, prb_pos);</span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> </span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> in line 344 of statistics_montecarlo(), for
the two-tailed test.</span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> </span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> Maybe it would be even better to compare the
absolute values of the</span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> observed and the randomized statistics, i.e.
doing something like this</span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> </span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> for i=1:Nrand,</span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> ....</span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> if tail == 0,</span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> prb_pos = prb_pos +
(abs(statobs)<abs(statrand));</span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> end</span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> ...</span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> end</span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> if tail == 0,</span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> stat.prob = prb_pos./Nrand;</span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> end</span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> </span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> </span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> What do you think?</span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> </span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> Many thanks in advance for your comments.</span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> Best regards,</span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> --Maren</span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> </span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> --</span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> Max Planck Institute for Human Cognitive and
Brain Sciences</span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> Dipl.-Phys. Maren
Grigutsch mailto:grigu@cbs.mpg.de</span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> Stephanstr.1a
http://www.cbs.mpg.de</span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> 04103 Leipzig,
Germany phone/fax: +49
341 9940-136/-260</span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> </span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> ----------------------------------</span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> The aim of this list is to facilitate the
discussion between users of the FieldTrip</span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> toolbox, to share experiences and to discuss new
ideas for MEG and EEG analysis.</span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> See also http://listserv.surfnet.nl/archives/fieldtrip.html
and</span></font></p>
<p class=MsoPlainText><font size=3 face="Bookman Old Style"><span
style='font-size:12.0pt'>> http://www.ru.nl/fcdonders/fieldtrip.</span></font></p>
</div>
</body>
</html>
<p>----------------------------------</p>
<p>The aim of this list is to facilitate the discussion between users of the FieldTrip toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis.</p>
<p> http://listserv.surfnet.nl/archives/fieldtrip.html</p>
<p> http://www.ru.nl/fcdonders/fieldtrip/</p>