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Hi, Mark Thanks for your response. It seems to me, however, that I'm not out of the woods yet--because once I drop the missing EVs for any given run, that run will then not have the same number of contrasts. Have I misunderstood you somewhere? Best, Sam On Jun 3, 2004, at 11:15 AM, Mark Jenkinson wrote: > Hi, > > What you really need to do is create consistent *contrasts* not EVs. > It is contrasts that get fed up into the higher level analyses, not > EVs. > If an EV is missing, then do not have it in the model. However, when > formulating your contrasts make sure that the numbering of the > contrasts > is the same in each subject/session so that these feed up consistently. > > You'll have to be careful to select the appropriate EVs each time, as > their numbering will change whenever some are missing. > For example, if you had a contrast like 1 0 -1 0 0 1 0 and in one case > EV2 was missing then the design matrix would only have 6 columns, > not 7, and the contrast would become 1 -1 0 0 1 0 in this > instance (assuming the other EVs were present). > > Obviously these missing EVs cannot contribute to the contrast, but > as long as each contrast contains at least one EV then you are fine. > > All the best, > Mark > > > Sam Harris wrote: > >> I'm attempting to analyze event-related data acquired on 14 subjects, >> 3 runs each, in which >> certain EVs, in any given run, were not represented. For example, >> subject #6, in run #2, may not >> have provided a single example of EV 8 (while all other subjects did, >> as did subject #6 himself in >> runs 1 and 3). I'm wondering if there is any way of creating a >> "place-holder" model (in three- >> column format), so that all subjects and all runs can contain the >> same number of EVs, thereby >> allowing analysis at the group level. Could I, in the above case, >> create a spurious model for EV 8 >> (in subject #6, run #2), with a fictional onset time and duration, >> and scale it at (or near) 0? Or >> could I create an extra volume, tacked onto to the end of all scans, >> that represented the average >> value of each functional run, and then reference this timepoint in my >> model as a dummy-EV? >> Needless to say, I'm looking for a solution that will produce, in the >> worst case, a type 2 error. >> >> Thanks for your help. >> Sam >> >> >