Date:         Wed, 10 Nov 2004 10:23:21 -0800
Reply-To:     cassell.david@EPAMAIL.EPA.GOV
Sender:       "SAS(r) Discussion" <SAS-L@LISTSERV.UGA.EDU>
From:         "David L. Cassell" <cassell.david@EPAMAIL.EPA.GOV>
Subject:      Re: Logistic Regression Question
In-Reply-To:  <A7D4140CA0A3D24CA55F8A4495F1B2510606A209@argon.dcri.duke.edu>
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"DePuy, Venita" <depuy001@DCRI.DUKE.EDU> sagely replied:
> My understanding is that Catmod is a) painful, b) geared toward
multinomial
> logit regression, and c) can be accomplished in Genmod.

More-or-less true.

[A] CATMOD is older, and not as flexible.  It's so old that my wife
used it in her doctoral dissertation.  (Why does that sound vaguely as
if Rodney Dangerfield should be saying it, followed by a rimshot? :-)

[B] It's still fairly useful.  You can do logits, generalized logits,
cumulative logits, means, proportions, blah blah blah.  BUT you can't
really control the estimation method.  You get MLE with logits and
generalized logits, and weighted least squares (but NOT the sample
weights
as in this thread!) elsewhere.  GENMOD and other, newer, procs are more
flexible.

[C] Pretty much.

> Why don't you try proc surveyreg? Although I don't know that it will
do
> logistic.

It won't.  But you're dead on.  The survey design effects have to be
accounted
for.  PROC SURVEYLOGISTIC (SAS 9.1) is made for this problem.

> At any rate, you can do logistic regression in Genmod with a logit
link, and
> I believe it has more options than Proc Logistic does.

But doing all the mucking around to adjust for survey design effects in
the
variance-covariance matrix is a headache, and that still doesn't take
into
account all the other problems implicit in trying to wedge the survey
design
paradigm into a model-based paradigm.  Like the lack of proper domain
analysis.

> Don't do survey stuff myself, so perhaps someone else can speak to
that end
> of things.

Like anyone around here can get me to shut up.  :-)

David
--
David Cassell, CSC
Cassell.David@epa.gov
Senior computing specialist
mathematical statistician