Date: Wed, 1 Aug 2007 08:49:24 -0700
Reply-To: Paul Miller <pjmiller_57@YAHOO.COM>
Sender: "SAS(r) Discussion" <SAS-L@LISTSERV.UGA.EDU>
From: Paul Miller <pjmiller_57@YAHOO.COM>
Subject: PROC GENMOD: Specifying the Working Correlation Matrix for
Repeated Measures Data
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I'm running some GEE models using PROC GENMOD. My criterion variables consist of repeated lipid measures (cholesterol, triglycrides, total cholesterol to hdl ratio) from a sample of HIV patients. Values for each criterion are coded as 0 for normal and 1 for elevated. Lipids in HIV patients are often affected by the antiretroviral drugs they are taking. So I'm using a variety of arvs to predict whether or not patients had elevated lipids.
At this point, I'm wondering how I should specify the "working correlation matrix." I know that "exchangeable" is the most common structure, but I'm finding that my models sometimes crash ("Error in computing the variance function") when it is used. In contrast, the models seem to be better behaved when I use an "autoregressive" structure. Also, I was thinking that this structure might make more sense for repeated observtion within subjects as opposed to data where subjects are nested within groups. Is my thinking right here? Or apriori would people have been inclined to recommend the more commonly used exchangeable structure?
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