gee performs estimation of parameters in a restricted mean
model using standard GEEs with independent working correlation matrix. For
clustered data, cluster-robust standard errors are calculated. When
cond=TRUE, cluster-specific
intercepts are assumed.
gee(formula, link = c("identity", "log", "logit"), data, cond = FALSE,
clusterid, rootFinder = findRoots, ...)An expression or formula representing the expected outcome conditional on covariates.
A character string naming the link function to use. Has to be
"identity", "log" or "logit". Default is "identity".
A data frame or environment containing the variables appearing in
formula. If missing, the variables are expected to be found
in the environment of the formula argument.
A logical value indicating whether cluster-specific intercepts should
be assumed. Requires a clusterid argument.
A cluster-defining variable or a character string naming a
cluster-defining variable in the data argument. If it is not
found in the data argument, it will be searched for in the
calling frame. If missing, each observation will be considered to be
a separate cluster. This argument is required when cond = TRUE.
A function to solve a system of non linear equations. Default
is findRoots.
Further arguments to be passed to the function rootFinder.
gee return an object of class gee containing:
Estimates of the parameters.
Robust variance of the estimates.
The matched call.
The outcome vector.
The design matrix. For conditional methods there is no column corresponding to the intercept.
An estimation object returned from the function specified
in the rootFinder, if this function is called.
The residuals from the estimating equations.
The derivative of the residuals from the estimating equations.
Estimates parameters in a regression model, defined by
formula. When cond=FALSE, the estimated coefficients are
identical to those obtained with glm, but since no
distributional assumptions are made, a robust variance is
calculated. When cond=TRUE and link is "identity"
or "log", the coefficients will be calculated
using conditional estimating equations as described in Goetgeluk and
Vansteelandt (2008). When cond=TRUE and link="logit",
the coefficients will be calculated by conditional logistic regression
(with robust standard errors).
Goetgeluk S., & Vansteelandt S. (2008), Conditional generalized estimating equations for the analysis of clustered and longitudinal data. Biometrics, 64(3), pp. 772--780.
glm