[R-meta] sandwhich estimator with geeglm object

James Pustejovsky jepu@to @end|ng |rom gm@||@com
Mon May 1 16:55:04 CEST 2023

Hi Yefeng,

geeglm is currently available in the development version of clubSandwich.
We are including support for GEE models because clubSandwich implements
small-sample corrections to the sandwich variance estimator and to the
degrees of freedom, which are not available in geepack. McCaffrey and Bell
(2006; https://doi.org/10.1002/sim.2502) showed that these small-sample
corrections perform better than the standard sandwich estimators and
large-sample test statistics implemented in geepack.

GEE is not equivalent to GLS. Rather, geepack::geeglm() is to glm() as
nlme::gls() is to lm(). GEE models allow non-linear link functions for the
conditional expectation of the outcome. Of course, gls is a special case of
geeglm with an identity link function (just as lm is a special case of


On Mon, May 1, 2023 at 4:15 AM Yefeng Yang via R-sig-meta-analysis <
r-sig-meta-analysis using r-project.org> wrote:

> Dear experts,
> I would be grateful if anyone can address my confusion concerning robust
> variance estimation (especially via the implementation of clubsandwich
> package).
> First question:
> geeglm object refers to the regression model fitted by Generalized
> Estimating Equations (GEE), which can be implemented in package geepack.
> Given that GEE already calculates cluster robust errors to account for
> mids-specified var-cov structure (e.g., autocorrelation), why clubsandwich
> still calculate robust errors for geeglm object
> Second question:
> GEE basically relaxes the assumption about var-cov structure and it uses a
> working var-cov structure (usually misspecified) to get beta coefficient
> and then uses the sandwich estimator to estimate sampling variances
> Var(beta) or standard error SE(beta). In this sense, GEE is equivalent to
> generalized least squares (say fitted by gls()) with CRVE. Am I correct?
> Best,
> Yefeng
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