Hi - I presume you mean for combining, at second level, across difference
sessions for a given subject - yes, ME stage 1 is the best thing to use
for that (see the FEAT manual on the web for examples of how to do this if
you only have a few sessions per subject).
Cheers.
On Fri, 21 Oct 2005, Theo van Erp wrote:
> Would running "Mixed Effects Stage 1 only" lead to incorrect results when
> used for combining the single subject runs (maybe only to be used when
> combining runs from multiple subjects with run as a repeated and subject as
> random factor)?
>
> Tx, Theo
>
> on 10/17/05 7:46 AM, Stephen Smith at [log in to unmask] wrote:
>
> > Hi Theo, yes, this all makes sense:
> >
> > You can either follow the mixed inputs instructions at:
> > http://www.fmrib.ox.ac.uk/fslfaq/#feat_mixedup
> >
> > Or just run a "fake" 2nd level on these single cases using fixed-effects
> > (though you'll need to save the design.fsf and edit it by hand to change
> > the number of inputs to 1).
> >
> > Cheers. Steve.
> >
> >
> >
> > On Thu, 13 Oct 2005, Theo van Erp wrote:
> >
> >> Hi,
> >>
> >> I have another question related to empty EVs. I'm working on a single trial
> >> study with multiple runs and analyses based on subject responses.
> >>
> >> Sometimes there are missing EVs because a subject did not make a certain
> >> type of response. This is not a problem, since as suggested below I then
> >> leave out the empty Evs and leave the contrast order the same. I put zeros
> >> for the non-existent contrasts (due to the missing EV) and correct the
> >> contrasts to account for having fewer EVs. This appears to generate empty
> >> (0) copes, and I then combine only the non-empty copes in a 2nd level
> >> analysis to create 1 cope per subject to be included in a 3rd level
> >> analysis.
> >>
> >> However, I'm running into a problem when a contrast only exists in 1 run
> >> (you can't do a 2nd level, since the dof would be 0). Should I in this case
> >> just register the cope from one individual run to standard space in the
> >> first level analysis such that I can include it into a 3rd level analysis or
> >> does this somehow mess up the dofs?
> >>
> >> I'll try a couple of things, but any feedback would be appreciated.
> >>
> >> Best, Theo
> >>
> >> on 6/5/04 12:17 PM, Mark Jenkinson at [log in to unmask] wrote:
> >>
> >>> Hi,
> >>>
> >>> This depends on what contrasts you are trying to use.
> >>> If you have a contrast that only contains "missing" EVs then
> >>> you can't have this if you drop these EVs. However, I'm
> >>> assuming that the contrasts of interest for the group analysis
> >>> are not going to include only missing EVs for any subject or
> >>> session. Otherwise there is no information that this subject
> >>> or session can contribute to the group analysis in this case
> >>> and just shouldn't be included for the higher level analysis.
> >>>
> >>> If you do make contrasts to see certain effects in the lower
> >>> level analysis that you don't pass up to the group analysis
> >>> (e.g. a 0 0 1 0 0 ... 0 type contrast for each EV) then it doesn't
> >>> matter what you put in this place for the lower level analysis
> >>> as far as the group analysis is concerned.
> >>>
> >>> The best approach for you is probably to restrict yourself to
> >>> first level analyses that only contain the contrast of interest
> >>> for the group analysis. This should include at least one
> >>> non-missing EV for each session/subject (if not, exclude
> >>> that session/subject from the group analysis). Once you've
> >>> done this the group analysis is straightforward.
> >>>
> >>> If you are interested in looking at other contrasts in the lower
> >>> level, you can always run different contrasts again under
> >>> post-stats to have a look (which is quick and easy).
> >>>
> >>> All the best,
> >>> Mark
> >>>
> >>>
> >>> On Thursday, June 3, 2004, at 10:42 pm, Sam Harris wrote:
> >>>
> >>>> 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
> >>>>>>
> >>>>>>
> >>>>>
> >>>
> >>
> >> _____________________________________________________________
> >> Theo van Erp
> >> Lab Manager, PhD Candidate
> >>
> >> Cannon Lab
> >> Department of Psychology [log in to unmask]
> >> University of California Los Angeles voice (310) 794-9673
> >> 1285 Franz Hall, room 5556 fax (310) 794-9740
> >> Los Angeles, California, 90095-1563
> >> http://www.bol.ucla.edu/~vanerp
> >> _____________________________________________________________
> >>
>
> Best, Theo
>
> _____________________________________________________________
> Theo van Erp
> Lab Manager, PhD Candidate
>
> Cannon Lab
> Department of Psychology [log in to unmask]
> University of California Los Angeles voice (310) 794-9673
> 1285 Franz Hall, room 5556 fax (310) 794-9740
> Los Angeles, California, 90095-1563
> http://www.bol.ucla.edu/~vanerp
> _____________________________________________________________
>
--
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
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