Dear Stephen,
I quite agree that following Euclidean normalization (and subsequent
mean-centering) the betas for two different parametric regressors might not
be directly comparable. As you point out, the two regressors are not scaled
by the same factor when using a Euclidean transformation. So, it sounds as
if you agree with my concerns regarding the use of Euclidean normalization
for parametric regressors, at least for cases where an experimenter wants to
explicitly compare the betas for two different parametric regressors. Is
that right?
If so, what would be the best transformation to use if one wanted to
directly compare the betas for two parametric regressors?
As to my question of whether there is any reason to prefer a Euclidean
normalization or a Z-transformation of the parametric values, I don't quite
understand your statement that the z-transformation is not linear since, in
fact, the z-transformation is linear.
Thanks very much for the response!
Daniel
Daniel Weissman
Center for Cognitive Neuroscience
Duke University
Durham, NC 27705
|