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Abstract Details
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Activity Number:
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518
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Type:
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Contributed
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Date/Time:
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Wednesday, August 3, 2011 : 10:30 AM to 12:20 PM
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Sponsor:
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ENAR
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| Abstract - #302973 |
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Title:
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Estimating Equations for Regression Models with Cluster-Specific Intercepts
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Author(s):
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Kunthel By*+ and Bahjat Qaqish
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Companies:
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The University of North Carolina and
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Address:
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Department of Biostatistics, Chapel Hill, NC, 27599,
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Keywords:
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biased sampling ;
correlated data ;
GEE ;
nuisance parameters
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Abstract:
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GEE is not feasible for marginal models having cluster-specific intercepts. Imposing a mixing distribution on the intercepts offers a possible solution provided that generalized linear mixed model assumptions are satisfied. When these assumptions are not met, parameter estimates are generally biased. A simple procedure for constructing estimating equations is proposed that enable consistent estimation of parameters associated with cluster-varying covariates and is applicable regardless of whether cluster-specific intercepts are treated as fixed or random. Connections to conditional likelihoods and the Cox model are discussed. An application to outcome-dependent sampling based on cluster totals is proposed; knowledge of the sampling rates is not required. We show how existing software can be used to implement our estimating equations.
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