Date:         Wed, 18 Feb 2004 15:59:17 -0500
Reply-To:     Jay Weedon <jweedon@EARTHLINK.NET>
Sender:       "SAS(r) Discussion" <SAS-L@LISTSERV.UGA.EDU>
From:         Jay Weedon <jweedon@EARTHLINK.NET>
Organization: http://extra.newsguy.com
Subject:      Re: Zero Inflated Poisson Models in SAS (repeated measures)
Content-Type: text/plain; charset=us-ascii

On 18 Feb 04 20:34:57 GMT, afdbn@UAA.ALASKA.EDU (David Neal) wrote:

>The design involves three treatment groups that were measured pre, post,
>follow-up 1(3month), follow-up 2(6 month), follow-up 3(12 month).  There
>were literally hundreds of variables collected on each subject for each time
>period.(I guess they were going for the shotgun effect)  Several of the
>variables involve counts that have high frequencies of zeros.  We are trying
>to narrow the focus a bit before we start any sort of an analysis so I
>expect to be dealing with a smaller subset of variables.  I'm coming into
>the project on the back end so I'm not quite up to speed on all the oddities
>of the data but my initial impression is that a ZIP model would be an
>appropriate choice.

It might well be, but if the non-zero observations tend mostly to be
small frequencies (1s & 2s) it might be methodologically simpler to
dichotomize the outcomes as 0 vs >0, and going with a generalized
mixed linear model or a generalized estimating equations model. Do you
have a lot of missing data?

How you're going to deal with hundreds of outcomes is a different
problem!

JW