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Hi - this all sounds fine - and hopefully the advice on the FAQ will still work for the latest version of FEAT - let us know if not: http://www.fmrib.ox.ac.uk/fslfaq/#feat_mixedup Cheers. On 20 Mar 2010, at 17:56, James Reilly wrote: > FSL Listserve: > > I have an event related design in which I am modeling effects > corresponding > to 3 separate events/phases of a task. I have 2 groups (patients vs. > controls) with different Ns and for some subjects in each group, two > consecutive task runs (unfortunately, not all subjects received 2 > runs, but > there are an equal number of total runs between groups). I would > like to > include both runs for those subject that have them (create a mean > for that > subject) and combine these with subjects who received only one run, > and > then conduct a group comparison. If not for different number of > runs between > subjects, I think that this would be a straightforward example of a > multi- > session, multi-subject repeated measure analysis. Since it is not, > below is the > analysis strategy that I am planning. > > 1.) Run a 1st level analysis for each run for all subjects (some > will have a > single run, some will have two), with MCFLIRT on to conduct motion > correction > specific to each run. > > 2.) For subjects with 2 runs, conduct a 2nd level analysis in which > the lower > level feat directories from run1 and run2 are the specified inputs. > A fixed > effect model is specified and a single EV is coded as follows: > > Group EV1 > Input 1 (run1) 1 1 > Input 2 (run2) 1 1 > > This is I believe will provide a subject’s average activation across > the 2 runs, > generating 3 cope.feat directories corresponding to the 3 event/ > phases I am > interested in modeling. > > 3.) Conduct a 3rd level analysis using a mixed effect model with > inputs from > the 1st (for single run subjects) and 2nd (for two run subjects) level > analyses. Group membership is now included as an EV and relevant > contrasts > are coded to examine Control > Patient and Patient>Control > differences. > > What I am not clear on is how I can combine the *.feat directories > from the > 1st level analyses for subjects who have a single run with the > cope*.feat > directories from the 2nd level analyses for subjects with 2 runs as > the inputs > to this 3rd level analysis. > > To generate cope*.feat directories for subject with only one run, I > had > considered entering run1 twice and then zeroing this out as below, > but I am > not sure what consequences that will have on variance estimates etc > and it > just doesn’t seem correct. > Group EV1 > Input 1 (run1) 1 1 > Input 2 (run1) 1 0 > > I’d appreciate any guidance on this and/ or any suggestions or > comments if > this analytic approach seems off base. > > Thanks, > Jim > --------------------------------------------------------------------------- Stephen M. Smith, Professor of Biomedical Engineering Associate Director, Oxford University FMRIB Centre FMRIB, JR Hospital, Headington, Oxford OX3 9DU, UK +44 (0) 1865 222726 (fax 222717) [log in to unmask] http://www.fmrib.ox.ac.uk/~steve ---------------------------------------------------------------------------