Generalized Estimating Equations

By Geert Molenberghs. Methods of Information in Medicine, 2010

756 citations recorded by the source corpus.

Subfields: Control and Systems Engineering

View Paper: https://www.semanticscholar.org/paper/36a0fc50f581355eea5b007dec3c3de2c698ed95

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In Control and Systems Engineering

Citations in the corpus

False Memories of Fabricated Political Events (2013, methodology): “GEE is a regression approach that allows for repeated measurements within participants (see, e.g., Hardin & Hilbe, 2003).”
Inference for Misspecified Models With Fixed Regressors (2014, methodology): “We focus on the justidentified case, although the results can be extended to overidentified generalized method of moment (GMM) settings, for example, using empirical likelihood approaches (e.g., Qin and Lawless 1994; Imbens 1997; Imbens, Johnson and Spady 1998; Newey and Smith 2004).”
Critical success factors for the sustainability of Kaizen event human resource outcomes: An empirical study (2011, methodology): “0, and the Wald–Wolfowitz run test (Hardin and Hilbe, 2003) 5.”
Consistent model selection and data‐driven smooth tests for longitudinal data in the estimating equations approach (2009, methodology): “There have been many important developments of GEEs since the work of Liang and Zeger; see Diggle et al. (2002) and Hardin and Hilbe (2003).”
Silent Reading of Direct versus Indirect Speech Activates Voice-selective Areas in the Auditory Cortex (2011, neutral): “The 1% difference was not significant ( p > .4 by logit binomial generalized estimating equations [GEE]; Hardin & Hilbe, 2003).”
Bayesian Multilevel Analysis and MCMC (2008, background): “[44]; these authors chose a random sample of J = 65 schools (factor S) from the Inner London Education Authority in the late 1980s and then sampled a total of 4,059 16-year-old pupils (factor P ) at random from the chosen schools (a”
Multilevel and related models for longitudinal data (2008, background): “Examples include the Bahadur [2] and Dale [13] models, which parameterize dependence via marginal correlations and marginal bivariate odds-ratios, respectively [19, 44].”
Spatial models for distance sampling data: recent developments and future directions (2013, background): “Spatial autocorrelation can be accounted for via approaches that explicitly introduce correlations such as generalized estimating equations (GEEs; Hardin & Hilbe 2003) or generalized additive mixed models or via mechanisms such as that of Skaug (2006), which allow observations to cluster according…”
Accounting for uncertainty in ecological analysis: the strengths and limitations of hierarchical statistical modeling. (2009, methodology): “Common approaches for estimation of P include the Expectation-Maximization (E-M) algorithm, conditional and pseudo-likelihood methods, and estimating equations (Hardin and Hilbe, 2003).”