Date: Fri, 10 Oct 2003 09:35:18 -0700
Reply-To: Allison Ellman <allison@QUONET.com>
Sender: "SPSSX(r) Discussion" <SPSSX-L@LISTSERV.UGA.EDU>
From: Allison Ellman <allison@QUONET.com>
Subject: Re: test for this IV, these DVs and covars
Content-Type: text/plain; charset="us-ascii"
Are you saying that the covariates are categorical? I think the proper
way to handle them is to make dummy variables (a set of dichotomous
variables coded 0 for all categories except one) For instance, for race,
a dummy variable Caucasian will equal 0 for everyone except Caucasians
for which it will equal 1. africanamerican will equal 0 for everyone
except African Americans. Etc. Then, all but one of the dummy variables
are included in the model (the one left out is the reference group.
Hope this helps.
. . .
From: Nico Peruzzi, Ph.D. [mailto:firstname.lastname@example.org]
Sent: Friday, October 10, 2003 9:20 AM
Subject: test for this IV, these DVs and covars
I've got myself a little confused and am hoping someone can
guide me back onto track.
My main factor (drug group) has three levels.
I have 5 numeric outcomes measures of interest.
I have a number of covariates (both numeric and
I want to examine the effect of my main factor on the
outcome variables, while removing the influence of the
Seems simple enough, but I find that the GLM models seem to
specify using only numeric covariates. I then thought
about using DISCRIM, but got confused as how to step in the
outcomes measures versus the covariates, and well, here I
Any guidance would be greatly appreciated.
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