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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:"Calibri","sans-serif";color:#1F497D'>Hi Valerie,<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'>A dependent samples t-test (also called paired-samples t-tests) involves pairs of observations. If you have 20 trials in one subject, 10 in condition A and 10 in condition B, what would be your pairs (i.e., in which natural way would you construct pairs)?<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'>It may good to also read one of our papers before starting with the tutorial. The concept of a UO is not specific to permutation-based statistics, and given that your problem seems to be with this concept, you could try Maris_Psychophysiology_2012, which starts out with classical statistical tests. For cluster-based permutation statistics itself, Maris&Oostenveld_JNM_2007 is the better choice.<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'>Best, <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'>Eric Maris<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 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"'> Valerie Nunez [mailto:vnune@hunter.cuny.edu] <br><b>Sent:</b> donderdag 3 oktober 2013 16:23<br><b>To:</b> fieldtrip@science.ru.nl<br><b>Subject:</b> [FieldTrip] Cluster-level permutation test statistics<o:p></o:p></span></p></div></div><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal>Hello,<o:p></o:p></p><div><p class=MsoNormal><o:p> </o:p></p><div><p class=MsoNormal>I'm a little confused about the notion of unit of observation (UO) as subject or trial in the cluster_permutation_timelock tutorial:<o:p></o:p></p></div><div><p class=MsoNormal><a href="http://fieldtrip.fcdonders.nl/tutorial/cluster_permutation_timelock">http://fieldtrip.fcdonders.nl/tutorial/cluster_permutation_timelock</a><o:p></o:p></p></div><div><p class=MsoNormal><o:p> </o:p></p></div><div><p class=MsoNormal>Specifically, I don't quite understand how the example of congruent and incongruent trials for a single subject is considered a between-trials design and therefore uses an independent t-test. If two trials have taken place for one subject, why isn't this considered a within-subject design, thereby requiring a dependent-samples t-test?<o:p></o:p></p></div><div><p class=MsoNormal><o:p> </o:p></p></div><div><p class=MsoNormal>What am I missing?<o:p></o:p></p></div><div><p class=MsoNormal><o:p> </o:p></p></div><div><p class=MsoNormal>Thanks,<o:p></o:p></p></div><div><p class=MsoNormal><o:p> </o:p></p></div><div><p class=MsoNormal>Valerie<o:p></o:p></p></div></div></div></div></body></html>