Working correlation structure misspecification, estimation and covariate design: Implications for generalised estimating equations performance

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Generalized Estimating Equations in Longitudinal Data Analysis: A Review and Recent Developments (2014, unknown): “But, correctly specifying “working” correlation structure can definitely enhance the efficiency of the parameter estimates in particular when the sample size is not large enough [16, 24, 25, 29].”
Consistent model selection and data‐driven smooth tests for longitudinal data in the estimating equations approach (2009, background): “See also the recent work of Hall and Severini (1998), Shults and Chaganty (1998), Stoner and Leroux (2002) and Wang and Carey (2003).”
Improved Generalized Estimating Equation Analysis via xtqls for Quasi–Least Squares in Stata (2007, unknown): “However, incorrect application of an identity structure can cause loss in efficiency in estimation of the regression parameter, especially when the true correlations are large; e.g., see Sutradhar and Das (2000) and Wang and Carey (2003).”
Longitudinal Data Analysis. Handbooks of Modern Statistical Methods (2009, background): “One set of estimating equations for α that has generated some interest in the statistical literature is that based on the notion of “Gaussian” estimation (see, for example, Lipsitz, Laird, and Harrington, 1992; Lee, Laird, and Johnston, 1999; Hall and Severini, 1998; Lipsitz et al., 2000; Fitzmauric”