Rik/Bas/List
Has anybody actually tested in a quantitative way the impact of these
somewhat (we know - but how much?) inefficient first level betas on a 2nd
level inference?
It also seems a recurring question how white one should wash one's
residuals...
Alexa
> >
> > In the absence of correlation, the inclusion of extra basis functions
> > can reduce the residual error in 1st-level models, and hence improve
> > T-contrasts on one basis function alone (eg the canonical HRF).
> > However, the inclusion of such extra basis functions will not affect
> > 2nd-level analyses on only one basis function in SPM99, or only
> > minimally so in SPM2/5, because this orthogonality means that the
> > parameter estimates are not affected under OLS, and only minimally
> > under WLS. Thus it is a common misapprehension that including, eg the
> > temporal derivative of the canonical HRF in 1st-level models somehow
> > allows for latency differences in 2nd-level analyses on the canonical
> > HRF alone. It does not. The answer is to take (contrasts of) all basis
> > functions to 2nd-level analyses, and again perform F-contrasts.
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