View source: R/clustered-robust.R
vcovCR | R Documentation |
Robust estimation of the covariance matrix of the coefficient estimates in regression models with clustering.
vcovCR(x, cluster = NULL, type = c("CR", "CR0", "CR1"))
x |
A fitted model object. |
cluster |
A variable or expression giving the cluster for each observation. |
type |
A character string specifying the estimation type. For details see below. |
The default type
of "CR" uses the same adjustment as 'Stata'.
The values of "CR0" and "CR1" are analogous to "HC0" and "HC1",
respectively, in vcovHC
.
A matrix containing the covariance matrix estimate with attribute
type
giving the type
option used in estimating it.
See Also robust.summary
and vcovHC
.
clotting <- data.frame( cl = rep(1:2,each=9), u = c(5,10,15,20,30,40,60,80,100), lot = c(118,58,42,35,27,25,21,19,18, 69,35,26,21,18,16,13,12,12)) clot.model <- glm(lot ~ log(u), data = clotting, family = Gamma) vcovCR(clot.model, cluster=cl) data(swiss) model1 <- lm(Fertility ~ ., data = swiss) ## These should give the same answer vcovCR(model1, cluster=1:nobs(model1), type="CR0") sandwich::vcovHC(model1, type="HC0")
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