Dear SPM users
we had a very intensive discussion about whether it is appropriate
to use nominal or ordinal scaled covariates in SPM. In statistics,
we had learnt that covariates have to be at least intervall scaled
in order to be used as a real covariate in a design because the regression
model
needs continnous values. But, there are many situations where the covariates
used
are nominal scaled (e.g., gender, different scanners, other dichotome
variables
like genetic mutations, SNPs (yes/no coded).
Is there a special implementation in SPM that allows the use of nominal
scaled
variables as covariates?
If yes, how does the influence of a dichotome variable is computed out of
the data
(with a normal regression model)?
Outside of SPM, I had seen correlations where one variable is intervall
scaled (e.g. brain volumes)
and the other nominal scaled (e.g. gender). Are these correlations really
appropriate?
Thanks a lot in advance
Best regards
Juergen
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Juergen Haenggi, Ph.D. student
Neuropsychology and Imaging
Division of Psychiatry Research
Psychiatric University Hospital
University of Zurich, Switzerland
P.O. Box 1931
Lenggstrasse 31, 8032 Zurich
0041 44 384 26 10 (office phone)
0041 76 445 86 84 (mobile phone)
0041 44 384 26 86 (fax)
H 115 (office room number)
[log in to unmask] (division email)
http://www.dpr.unizh.ch/ (division website)
http://www.juergenhaenggi.ch (private website)
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