Date: Wed, 17 Dec 2008 09:45:11 -0500
Reply-To: Art@DrKendall.org
Sender: "SPSSX(r) Discussion" <SPSSX-L@LISTSERV.UGA.EDU>
From: Art Kendall <Art@DrKendall.org>
Organization: Social Research Consultants
Subject: Re: Gram Schmidt orthogonalization procedure
In-Reply-To: <200812171307.mBHBl18i020280@malibu.cc.uga.edu>
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I have never seen centering done for adding a power term. However, a
power term is a form of interaction of a variable with itself. Based
on this definition perhaps you should do what you would do with any
other interaction term and center the x before squaring.
compute squareterm= (x-xmean) **2.
Is there a way for you to get a dependent variable at a better level of
measurement?
Art Kendall
Social Research Consultants
Dulce Subida wrote:
> Hi everyone!
>
> I need to get a Gaussian logistic model in SPSS, to predict the
> probability of occurence of a species (binary dependent variable) as a
> function of an environmental variable (x: continuous independent
> variable). I thought I could simply perform the binary logistic
> regression, using x and x2 as independent variables in the model. However
> in such case I think I will have a severe problem of multicollinearity
> (between x and x2). I thought I could orthogonalize both independent
> variables in order to surpass that problem. Does anyone know how can I run
> the Gram Schmidt orthogonalization procedure in SPSS, or does anyone know
> the syntaxis for it?
>
> Thank you a lot for your help!
>
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