Justine Shults () (Department of Biostatistics, University of Pennsylvania)
Abstract
Liang and Zeger's original formulation of generalized estimating equations (GEE) has been widely applied since its introduction in 1986 because it extends the application of generalized linear models to clustered data. In this presentation we discuss a method, quasi-least squares (QLS), that is in the framework of GEE and builds on this popular approach by allowing for consideration of correlation matrices that were previously difficult to apply. In particular, we describe how to QLS in a straight-forward fashion by making use of Stata's xtgee procedure. We then discuss some data analysis examples.
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