genZcor
constructs the design matrix for the correlation structures: independence, echangeable, ar1 and unstructured The user will need this function only as a basis to construct a user defined correlation structure: use genZcor to get the design matrix Z for the unstructured correlation and define the specific correlation structure by linear combinations of the columns of Z.
genZcor(clusz, waves, corstrv)
clusz |
integer vector giving the number of observations in each cluster |
waves |
integer vector, obervations in the same cluster with values of wave i and j have the correlation sigma_ij |
corstrv |
correlation structures: 1=independence,2=exchangeable,3=ar1, 4=unstructured |
|
the design matrix for the correlation structure |
Jun Yan jyan.stat@gmail.com
#example to construct a Toeplitz correlation structure
# sigma_ij=sigma_|i-j|
#data set with 5 clusters and maximally 4 observations (visits) per cluster
gendat <- function() {
id <- gl(5, 4, 20)
visit <- rep(1:4, 5)
y <- rnorm(id)
dat <- data.frame(y, id, visit)[c(-2,-9),]
}
set.seed(88)
dat<-gendat()
#generating the design matrix for the unstructured correlation
zcor <- genZcor(clusz = table(dat$id), waves = dat$visit, corstrv=4)
# defining the Toeplitz structure
zcor.toep<-matrix(NA, nrow(zcor),3)
zcor.toep[,1]<-apply(zcor[,c(1,4,6)],1,sum)
zcor.toep[,2]<-apply(zcor[,c(2,5)],1,sum)
zcor.toep[,3]<-zcor[,3]
zfit1 <- geese(y ~ 1,id = id, data = dat,
corstr = "userdefined", zcor = zcor.toep)
zfit2 <- geeglm(y ~ 1,id = id, data = dat,
corstr = "userdefined", zcor = zcor.toep)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.