If the covariates are collinear, then you can't properly estimate the
model. They are collinear if they explain the variance of each other.
I would first test for the relationship of your covariates before putting
them into the model as you don't want the covariates to be collinear.
Best Regards, Donald McLaren
=
D.G. McLaren, Ph.D.
Postdoctoral Research Fellow, GRECC, Bedford VA
Research Fellow, Department of Neurology, Massachusetts General Hospital
and
Harvard Medical School
Website: http://www.martinos.org/~mclaren
Office: (773) 406-2464
=
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On Wed, Jun 27, 2012 at 3:42 PM, mdkrue...@uwalumni.com
mdkrue...@uwalumni.com wrote:
Freesurfers-
Question, when looking for interactions to justify using DOSS say i am
looking at cortical thickness and i have two discrete variables (G1 and G2)
and 4 continious variables (V1, V2, V3, V4). My thinking is that i should
look to see if there are interactions with the groups and each individual
variable. However what if it is likely that an interaction of G1, G2, and
V1 can be explained by V2?
Michael
--
Michael D. Kruepke
PhD - University of Illinois at Urbana-Champaign
BA - Psych - University of Wisconsin-Madison
mdkrue...@gmail.com
(262)-483-7449
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