geeglm {geepack}R Documentation

Fit Generalized Estimating Equations (GEE)

Description

The geeglm function fits generalized estimating equations using the 'geese.fit' function of the 'geepack' package for doing the actual computations. geeglm has a syntax similar to glm and returns an object similar to a glm object. An important feature of geeglm, is that an anova method exists for these models.

Usage

geeglm(formula, family = gaussian, data=parent.frame(), weights, subset, 
                  na.action, start = NULL, etastart, mustart, offset,
                  control = geese.control(...), 
                  method = "glm.fit", x = FALSE, y = TRUE,
                  contrasts = NULL, 
                  id, waves=NULL, zcor=NULL, 
                  corstr = "independence",
                  scale.fix = FALSE,
                  scale.value =1, std.err="san.se",
                  ...) 

Arguments

formula See corresponding documentation to glm
family See corresponding documentation to glm
data See corresponding documentation to glm
weights See corresponding documentation to glm
subset See corresponding documentation to glm
na.action See corresponding documentation to glm
start See corresponding documentation to glm
etastart See corresponding documentation to glm
mustart See corresponding documentation to glm
offset See corresponding documentation to glm
control See corresponding documentation to glm
method See corresponding documentation to glm
x See corresponding documentation to glm
y See corresponding documentation to glm
contrasts See corresponding documentation to glm
id a vector which identifies the clusters. The length of `id' should be the same as the number of observations. Data are assumed to be sorted so that observations on a cluster are contiguous rows for all entities in the formula.
waves Wariable specifying the ordering of repeated mesurements on the same unit. Also used in connection with missing values. See examples below.
zcor Used for entering a user defined working correlation structure.
corstr a character string specifying the correlation structure. The following are permitted: '"independence"', '"exchangeable"', '"ar1"', '"unstructured"' and '"userdefined"'
scale.fix a logical variable; if true, the scale parameter is fixed at the value of 'scale.value'.
scale.value numeric variable giving the value to which the scale parameter should be fixed; used only if 'scale.fix == TRUE'.
std.err Type of standard error to be calculated. Defualt 'san.se' is the usual robust estimate. Other options are 'jack': if approximate jackknife variance estimate should be computed. 'j1s': if 1-step jackknife variance estimate should be computed. 'fij': logical indicating if fully iterated jackknife variance estimate should be computed.
... further arguments passed to or from other methods.

Value

~Describe the value returned If it is a LIST, use

comp1 Description of 'comp1'
comp2 Description of 'comp2'

...

Warning

geeglm has not been thoroughly tested. Please report bugs.

Note

See the documentation for the 'geese' function for additional information.

Author(s)

Søren Højsgaard, sorenh@agrsci.dk

References

Liang, K.Y. and Zeger, S.L. (1986) Longitudinal data analysis using generalized linear models. Biometrika, *73* 13-22.

Prentice, R.L. and Zhao, L.P. (1991). Estimating equations for parameters in means and covariances of multivariate discrete and continuous responses. Biometrics, *47* 825-839.

See Also

geese, glm,anova.geeglm

Examples

data(dietox)
dietox$Cu     <- as.factor(dietox$Cu)
mf <- formula(Weight~Cu*(Time+I(Time^2)+I(Time^3)))
gee1 <- geeglm(mf, data=dietox, id=Pig, family=poisson("identity"),corstr="ar1")
gee1
summary(gee1)

mf2 <- formula(Weight~Cu*Time+I(Time^2)+I(Time^3))
gee2 <- geeglm(mf2, data=dietox, id=Pig, family=poisson("identity"),corstr="ar1")
anova(gee2)




[Package geepack version 1.0-5 Index]