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Hi - yes, your reply had made it onto the list - but not in the place on the September listing that you expected because you sent it in reply to a different thread :) Yes, 1 and 2 make sense - though note that 2. should be a mixed-effects (FLAME stage 1) analysis if you are going to feed the results up to 3. 3. sounds fine too, though if you are only interested in the A-B contrast for each subject then you may as well just have all A and all B in the 2. analysis for each subject, get the [1 -1] contrast from that, and just feed that single value from each subject up into 3. Cheers. On Thu, 8 Sep 2005, N.M. van Strien wrote: > Hi Steve, > > I replied before on your answer, but since I dont see it on the > mailinglist I decided to post it again. > > First: thanks for your suggestions! > > I readily applied your fixed effects solution to my one subject problem. > However, if I continue this study more subjects will be sampled and a > mixed-effects model will be of interest to me. Is my approach (see below) > then the most efficient or would you suggest a different approach for this > analysis? > > 1. Single subject - per run analysis (creating 8 feat dirs) > 2. Single subject - grouping data over A fix A and over B fix B > runs (resulting in 2 gfeat dirs) > 3. Multi subject analysis having one EV for the A B difference, > plus an EV for each subject to model each subjects mean effect (similar to > the Paired Two-Group Difference example). > > Thanks, > > Niels > -- Stephen M. Smith DPhil Associate Director, FMRIB and Analysis Research Coordinator Oxford University Centre for Functional MRI of the Brain John Radcliffe Hospital, Headington, Oxford OX3 9DU, UK +44 (0) 1865 222726 (fax 222717) [log in to unmask] http://www.fmrib.ox.ac.uk/~steve