Dear Karl,
you responded to:
> In order to examine the effect of the covariate on brain
> perfusion/metabolism within subjects in SPM (which I believe is what
> correlating difference scans with difference psychometric measures
> does) you would have to model subject (to remove intersubject
> variance), not condition, but covariate, which would in the absence of
> a condition effect acount for the variance within subjects.
>
> If this is true, how do you configure the model within SPM to model
> only subject and covariate effects (remember there are two scans and
> two covariate measures per subject) without modelling condition?
with:
Simply use multi-subject, covariates only.
------
I have done this and it works. (SPM 96 and SPM "97" Windows).
Unfortunately my dataset gives identical results, when I use 2
conditions or 2 replications (1 condition). Which leads me to the
question: in which order are the various effects entered into the
model. Or in other words, are there effects that are estimated only
after other effects have been modelled? For example, confounds
first, then covariates of interest, then condition and subject effects -
or all simultaneously? By playing with the data, I found for example
that SPM estimates of condition effects vary with the covariate of
interest entered into the model, i.e. they seem to be computed after
the covariate of interest effect has been taken into account (or
simultaneously). - Condition effects are also identical whether the
covariate is entered as a confounder or a covariate of interest.
Many thanks for you help and forbearance
Klaus
Professor KP Ebmeier
Department of Psychiatry
University of Edinburgh
Edinburgh EH10 5HF
United Kingdom
Tel/Fax: *44-131-5376505
Website: www.pst.ed.ac.uk
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