Hi - I think I'm following the description, though I'm guessing that
EVs 3 and 4 should be swapped in your description. I don't understand
what "testversion" means, but it seems likely that the information
contained in testversion is rank deficient when compared with EVs 1-4
- is that possible?
Cheers.
On Thu, 22 Jul 2004, Goekoop, R. wrote:
> Dear all,
>
> I'm attempting to correlate functional effects of medication treatment to
> behavioral data. The study involves 18 patients, 3 sessions for each patient
> (corresponding to 3 medication regimes (A, B, C); so 3 measures for each
> patient).
>
> For this, I specified a higher level design involving 54 inputs (18 x 3), 1
> group, and 24 EVs. The first two EVs code for (randomized) medication
> regimes (B > A and C > A respectively; contrasts between these EVs yields C
> <> B). The second two EVs code for scanorder (session 2 > 1; session 3 > 1
> respectively). Next two EVs code for testversion (2 > 1 and 3 > 1
> respectively; randomized); The remaining 18 EVs put weights to data derived
> from the same subject (to account for pairedness of the data), i.e.:
>
> Inputs: Group EV1 EV2 EV3 EV4 EV5 EV6 EV7 EV8
> EV9....
>
> 1 1 -1 -1 -1 -1 0 1 1 0
> 0
> 2 1 0 1 1 0 -1 -1 1 0
> 0
> 3 1 1 0 0 1 1 0 1 0
> 0
>
> 4 1 0 1 -1 -1 1 0 0 1
> 0
> 5 1 -1 -1 1 0 0 1 0 1
> 0
> 6 1 1 0 0 1 -1 -1 0 1
> 0
>
> 7 ... 54: Etc.
>
> Now, I want to add an additional EV coding for (demeaned) MMSE scores (a
> neuropsychological scale), e.g.:
>
> EV 55:
>
> 3.5
> 3.5
> 3.5
>
> -2.5
> -2.5
> -2.5
>
> ...etc
>
> The design however becomes rank-deficient (something to the power of -17)
> as soon as I add this EV.
>
> I tried various approaches, the first one being to collapse my data by
> calculating differential images of regime-types (i.e. B > A and C > A) in a
> second level analysis, and entering these images as inputs in a third-level
> analysis for correlation with behavioral data. However, as soon as I try to
> regress out effects of either scanorder or testversion at second level (at
> which level the differential images are calculated), the design becomes rank
> deficient (again something ^ -17). I therefore stuck to calculating
> differential images at 2nd level and then tried to regress out effects of
> scanorder and testversion at 3rd level, while at the same time correlating
> data with behavioral scores.
>
> For this, I separated differential inputs (B > A) from (C > A) inputs and
> ran two separate third level analyses on these separate datasets. I thought
> this to be necessary, since putting these inputs together in one design
> would require additional EVs coding for pairedness of inputs derived from
> the same subject. This would bring the total number of EVs to 27, with
> number of inputs = 36, which I thought would not work well (please correct
> me if I'm wrong).
>
> Both separate 3rd level analyses worked well, however by now, collapsing of
> data had reduced the total number of inputs for each design to 18, while the
> number of EVs was 8. By now, nothing of my original effects of treatment
> survived (effects are rather small). Might this be due to data-collapsing
> and loss of DOF? Do I just demand too much of my data, or would there
> perhaps be an alternative solution to this problem? Any help would be
> greatly appreciated,
>
> Thanks,
>
> Rutger.
>
> Drs. R. Goekoop, MD.
> Department of Neurology
> Vrije Universiteit Medical Centre
> De Boelelaan 1117, P.O. Box 7057
> 1007 MB Amsterdam, the Netherlands
> Phone: 0031-20-4440316
> E-mail: <mailto:[log in to unmask]>
>
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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