vcov.glmgee: Estimate of the variance-covariance matrix in GEEs

Description Usage Arguments Value References Examples

View source: R/geeglm.R

Description

Computes the type-type estimate of the variance-covariance matrix from an object of the class glmgee.

Usage

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## S3 method for class 'glmgee'
vcov(object, ..., type = c("robust", "jackknife"))

Arguments

object

An object of the class glmgee which is obtained from the fit of a generalized estimating equation.

...

further arguments passed to or from other methods. For example, k, that is, the magnitude of the penalty in the QIC (or the QICu), which by default is set to be 2.

type

an (optional) character string indicating the type of estimator which should be used. The available options are: robust estimator ("robust"), jackknife estimator computed from the one-step approximations of the “leave-one-out” estimates of the parameter vector ("jackknife"). By default, type is set to be "robust".

Value

A matrix with the type-type estimate of the variance-covariance matrix.

References

Lipsitz S.R., Laird N.M. and Harrington D.P. (1990) Using the jackknife to estimate the variance of regression estimators from repeated measures studies. Communications in Statistics - Theory and Methods 19, 821–845.

Examples

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## Example 1
mod <- size ~ poly(days,4) + treat
fit1 <- glmgee(mod, id=tree, family=Gamma("log"), data=spruce, corstr="Exchangeable")
vcov(fit1)
vcov(fit1,type="jackknife")

## Example 2
mod <- dep ~ visit + group
fit2 <- glmgee(mod, id=subj, family=gaussian, corstr="AR-1", data=depression)
vcov(fit2)
vcov(fit2,type="jackknife")

## Example 3
mod <- depressd ~ visit + group
fit3 <- glmgee(mod, id=subj, family=binomial, corstr="Stationary-M-dependent(3)", data=depression)
vcov(fit3)
vcov(fit3,type="jackknife")

glmtoolbox documentation built on June 9, 2021, 9:07 a.m.