Date: Thu, 18 Dec 2008 02:35:44 -0500
Reply-To: Dulce Subida <dulcesubida@YAHOO.COM.BR>
Sender: "SPSSX(r) Discussion" <SPSSX-L@LISTSERV.UGA.EDU>
From: Dulce Subida <dulcesubida@YAHOO.COM.BR>
Subject: Re: Gram Schmidt orthogonalization procedure
Thank you for your help!
Yes I have continuous measures of the dependent variable (abudances per
m3), however my purpose at the moment is to model the presence/absence of
the species.
The Gaussian logistic model is ecologically meaningful and has been
already applied a few times to data sets similar to the one I am handling,
however I could not find any information about the problem of the
multicollinearity between the independent variable and its interaction
with itself. This problem is mentioned in some textbooks for polynomial
regression, and to me it seems that the gaussian logistic regression has
implicit a polynomial (of second order) regression (in the quadratic
response function that is fitted to the logistic equation). I will
probably perform the procedure with and without transformation of the data
and compare the estimates of the parameters... it is working the double
however...
Thank you again!
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