Hi Nikolaos,
when you mention "demean the data first", does it mean
that you simply run randomise with the -D option? If
yes, this is not enough: you also need to demean the 3
covariates in your model as it appears you haven't
done so.
Hope this helps,
Gwenaelle
--- Nikolaos Koutsouleris
<[log in to unmask]> a écrit :
> Der FSL'ers,
>
> I tried to estimate a VBM multiple regression design
> with randomise, which
> gave me unexpectedly high p values. As I am
> skeptical about my results, I am
> wondering if I made a mistake at some point:
>
> The following design with 1 covariate of interest
> (1st regressor) and two
> nuisance variables (2nd column: age & 3d column:
> global GM volume) was
> created with the GLM tool:
>
> %! VEST-Waveform File
> /NumWaves 3
> /NumPoints 28
> /PPheights 9.800000e-01 3.810000e+01 8.607700e+02
> /Matrix
> 7.900000e-01 2.824000e+01 6.572900e+02
> 8.800000e-01 2.600000e+01 6.204000e+02
> 7.400000e-01 2.942000e+01 7.207500e+02
> 8.100000e-01 2.494000e+01 7.028600e+02
> 9.800000e-01 2.460000e+01 6.524600e+02
> 9.300000e-01 2.275000e+01 5.986000e+02
> ...
>
> I was interested in positive and negative
> correlation between focal GM
> volume and regressor 1. Therefore, I created the
> following contrasts in Glm:
>
> %! VEST-Waveform File
> /ContrastName1 pos_pA
> /ContrastName2 neg_pA
> /NumWaves 3
> /NumContrasts 2
> /PPheights 8.410671e-01 8.410671e-01
> /RequiredEffect 4.138 4.138
> /Matrix
> 1.000000e+00 0.000000e+00 0.000000e+00
> -1.000000e+00 0.000000e+00 0.000000e+00
>
> I started randomise with the following parameters:
> * -c 2 and -C 2
> * 5000 permutations
> * Demean the data first
>
> I checked the order of my covariate values and the
> smoothed (10 mm FWHM),
> modulated gray matter partitions. They are ok. The
> cluster-level analyses
> result in a cluster that covers the entire cortex.
> Did I something wrong?
>
> Any help would be greatly appreciated...
> Cheers,
>
> Nikos
>
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