The Generalized Estimating Equations (GEE) proposed by Liang and Zeger (1986) have found considerable attention in the last years and several extensions have been proposed. This paper will give a more intuitive description how GEE have been developed during the last years. Additionally we will describe the advantages and disadvantages of the diierent parametrisations that have been proposed in ...

Correlated response data are common in biomedical studies. Regression analysis based on the generalized estimating equations (GEE) is an increasingly important method for such data. However, there seem to be few model-selection criteria available in GEE. The well-known Akaike Information Criterion (AIC) cannot be directly applied since AIC is based on maximum likelihood estimation while GEE is ...

A SAS/IML software program is described that computes regression diagnostics for generalized estimating equations. These diagnostics are computationally efficient and accurate approximations for the effect of deleting one observation or one cluster on individual regression coefficients (DFBETA) or on the overall fit of the model (Cook’s Distance). New formulae for the diagnostics are presented ...

We consider marginal semiparametric partially linear models for longitudinal/clustered data and propose an estimation procedure based on a spline approximation of the nonparametric part of the model and an extension of the parametric marginal generalized estimating equations (GEE). Our estimates of both parametric part and nonparametric part of the model have properties parallel to those of par...

The method of generalized estimating equations (GEE) is often used to analyze longitudinal and other correlated response data, particularly if responses are binary. However, few descriptions of the method are accessible to epidemiologists. In this paper, the authors use small worked examples and one real data set, involving both binary and quantitative response data, to help end-users appreciat...

GENERALIZED ESTIMATING EQUATION BASED ZERO-INFLATED MODEL WITH APPLICATION TO EXAMINING THE RELATIONSHIP BETWEEN DENTAL CARIES AND FLUORIDE EXPOSURES Sheng Xu April 16, 2013 In the study of dental caries, the number of caries is frequently characterized by over-dispersion and excessive zeros. In addition, the numbers of caries from the same subject are correlated. Zero-Inflated (ZI) regression ...

The most commonly used model selection criterion, Akaike’s Information Criterion (AIC), cannot be used when the Generalized Estimating Equations (GEE) approach is considered for analyzing multivariate binary response. Recently, a modified version of AIC (mAIC) which is based on quasi-likelihood function is proposed as a model selection criterion. This model selection criterion can be used in th...