Dear Dorian,
that probably means that you end up having too many variance components
in the specification of your model, and not enough degrees of freedom to
estimate their corresponding hyperparameters in ReML.
You can see how many components you have with
Review>Design>Explore>Covariance structure.
If you select dependent measurements between levels of your factors and
unequal variance, that is likely to be the case.
Bringing one contrast at a time at the second level and using one-sample
t-tests would prevent worrying about that.
Best regards,
Guillaume.
Dorian P. wrote:
> Dear all,
>
> As I didn't receive any answer, I am reposting this again.
>
> Does anybody know why the Design Orthogonality changes so much when I
> set variance "Unequal" to one of the factors in full factorial anova.
>
> There is a strong collinearity coming out between conditions that
> shouldn't have any relation with each other.
>
> Attached the designs with "Equal" and "Unequal" variance set.
>
> Thank you.
>
> Dorian
--
Guillaume Flandin, PhD
Wellcome Trust Centre for Neuroimaging
University College London
12 Queen Square
London WC1N 3BG
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