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</o:shapelayout></xml><![endif]--></head><body lang=EN-US link=blue vlink=purple><div class=WordSection1><p class=MsoNormal><span style='font-size:11.0pt;font-family:"Verdana","sans-serif";color:#1F497D'>Hi Ana,<o:p></o:p></span></p><p class=MsoNormal><span style='font-size:11.0pt;font-family:"Verdana","sans-serif";color:#1F497D'><o:p> </o:p></span></p><p class=MsoNormal><span style='font-size:11.0pt;font-family:"Verdana","sans-serif";color:#1F497D'>To compare coherence between conditions across subjects (instead of trials), you need a different statfun: depsamplesT (for a within-subjects design; subjects have participated in all conditions) or indepsamplesT (for a between-subjects design; subjects have participated in only one condition). Typically, this type of test is performed using power as the dependent variable, but exactly the same test is used for comparing coherence in a multiple-subject study. However, you will have to specify the cfg.parameter field when calling ft_freqstatistics such that it points to the data field that contains your coherence data (importantly, for a given reference channel).<o:p></o:p></span></p><p class=MsoNormal><span style='font-size:11.0pt;font-family:"Verdana","sans-serif";color:#1F497D'><o:p> </o:p></span></p><p class=MsoNormal><span style='font-size:11.0pt;font-family:"Verdana","sans-serif";color:#1F497D'>Good luck,<o:p></o:p></span></p><p class=MsoNormal><span style='font-size:11.0pt;font-family:"Verdana","sans-serif";color:#1F497D'><o:p> </o:p></span></p><p class=MsoNormal><span style='font-size:11.0pt;font-family:"Verdana","sans-serif";color:#1F497D'>Eric Maris <o:p></o:p></span></p><p class=MsoNormal><span style='font-size:11.0pt;font-family:"Verdana","sans-serif";color:#1F497D'><o:p> </o:p></span></p><div style='border:none;border-left:solid blue 1.5pt;padding:0cm 0cm 0cm 4.0pt'><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"'> Ana Navarro Cebrian [mailto:sabato45@hotmail.com] <br><b>Sent:</b> vrijdag 5 april 2013 23:56<br><b>To:</b> fieldtrip@science.ru.nl<br><b>Subject:</b> [FieldTrip] Nonparametric statistical testing of phase coherence<o:p></o:p></span></p></div></div><p class=MsoNormal><o:p> </o:p></p><div><p class=MsoNormal><span style='font-family:"Calibri","sans-serif"'><br>Hello everybody,<o:p></o:p></span></p><div><p class=MsoNormal><span style='font-family:"Calibri","sans-serif"'>I'd like to use the test proposed in Maris et al., 2007 (that I believe is implemented in statistics_montecarlo.m?). <o:p></o:p></span></p></div><div><p class=MsoNormal><span style='font-family:"Calibri","sans-serif"'>I'm calculating the difference in phase coherence between two conditions. The problem is that one condition has much less trials than the other, so I imagine the Montecarlo simulation would need to be across trials, in which case, I'd end up with a p-value for each individual subject, right? I'm not sure then how to apply this across subjects. The Maris et al. paper is very clear, but it only explains single subject analysis. <o:p></o:p></span></p></div><div><p class=MsoNormal><span style='font-family:"Calibri","sans-serif"'>I hope that makes any sense. I appreciate any help.<o:p></o:p></span></p></div><div><p class=MsoNormal><span style='font-family:"Calibri","sans-serif"'>Thanks,<o:p></o:p></span></p></div><div><p class=MsoNormal><span style='font-family:"Calibri","sans-serif"'>Ana <o:p></o:p></span></p></div><div><pre> <o:p></o:p></pre></div></div></div></div></body></html>