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% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/glm.R
\name{vcovCR.glm}
\alias{vcovCR.glm}
\title{Cluster-robust variance-covariance matrix for a glm object.}
\usage{
\method{vcovCR}{glm}(
obj,
cluster,
type,
target = NULL,
inverse_var = NULL,
form = "sandwich",
...
)
}
\arguments{
\item{obj}{Fitted model for which to calculate the variance-covariance matrix}
\item{cluster}{Expression or vector indicating which observations belong to
the same cluster. Required for \code{glm} objects.}
\item{type}{Character string specifying which small-sample adjustment should
be used, with available options \code{"CR0"}, \code{"CR1"}, \code{"CR1p"},
\code{"CR1S"}, \code{"CR2"}, or \code{"CR3"}. See "Details" section of
\code{\link{vcovCR}} for further information.}
\item{target}{Optional matrix or vector describing the working
variance-covariance model used to calculate the \code{CR2} and \code{CR4}
adjustment matrices. If a vector, the target matrix is assumed to be
diagonal. If not specified, the target is taken to be the estimated variance function.}
\item{inverse_var}{Optional logical indicating whether the weights used in
fitting the model are inverse-variance. If not specified, \code{vcovCR}
will attempt to infer a value.}
\item{form}{Controls the form of the returned matrix. The default
\code{"sandwich"} will return the sandwich variance-covariance matrix.
Alternately, setting \code{form = "meat"} will return only the meat of the
sandwich and setting \code{form = B}, where \code{B} is a matrix of
appropriate dimension, will return the sandwich variance-covariance matrix
calculated using \code{B} as the bread.}
\item{...}{Additional arguments available for some classes of objects.}
}
\value{
An object of class \code{c("vcovCR","clubSandwich")}, which consists
of a matrix of the estimated variance of and covariances between the
regression coefficient estimates.
}
\description{
\code{vcovCR} returns a sandwich estimate of the variance-covariance matrix
of a set of regression coefficient estimates from an \code{\link{glm}} object.
}
\examples{
data(dietox, package = "geepack")
dietox$Cu <- as.factor(dietox$Cu)
weight_fit <- glm(Weight ~ Cu * poly(Time, 3), data=dietox, family = "quasipoisson")
V_CR <- vcovCR(weight_fit, cluster = dietox$Pig, type = "CR2")
coef_test(weight_fit, vcov = V_CR, test = "Satterthwaite")
}
\seealso{
\code{\link{vcovCR}}
}
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