Generalized Estimating Equations (gee) for glm–type data

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Generalized Estimating Equations (gee)for glm type dataS ren H Research UnitDanish Institute of Agricultural SciencesJanuary 23, 2006Printed: January 23, 2006 File: Preliminaries32 Working example respiratory illness43 Correlated Pearson residuals94 Marginal vs. conditional models125 Marginal models for glm type data146 Estimating Equations for gee type Specifications needed for Deriving and solving Newton Estimation of the covariance of ........................ Model based Emperical estimate sandwich The working correlation Exploring different working correlations338 Comparison of the parameter When do GEEs work?.............................. What to do geeglm vs. 23, 2006page 231 PreliminariesThese notes deal with fitting models for responses of type oftendealt with with Generalized linear models (glm) but with thecomplicating aspect that there may be repeated measurementson the same approach here is Generalized Estimating Equations (gee).

The idea behind estimating functions is to find a function ψ(θ) which immitates the score function U(θ) = d dθ log p(y; θ). Let ψ(θ) = ψ(θ,y) be such a function denoted an estimating function. Solve (usually by iteration) the estimating equations ψ(θ) = 0 giving θˆ = θˆ(y) If E θ(ψ(θ)) = 0 for all θ (which holds for the ...

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