timereg (version 2.0.1)

recurrent.marginal.mean: Estimates marginal mean of recurrent events

Description

Fitting two aalen models for death and recurent events these are combined to prducte the estimator $$ \int_0^t S(u) dR(u) $$ the mean number of recurrent events, here $$ S(u) $$ is the probability of survival, and $$ dR(u) $$ is the probability of an event among survivors.

Usage

recurrent.marginal.mean(recurrent, death)

Arguments

recurrent

aalen model for recurrent events

death

aalen model for recurrent events

Details

IID versions used for Ghosh & Lin (2000) variance. See also mets package for quick version of this for large data mets:::recurrent.marginal, these two version should give the same when there are no ties.

References

Ghosh and Lin (2002) Nonparametric Analysis of Recurrent events and death, Biometrics, 554--562.

Examples

# NOT RUN {
### get some data using mets simulaitons 
library(mets)
data(base1cumhaz)
data(base4cumhaz)
data(drcumhaz)
dr <- drcumhaz
base1 <- base1cumhaz
base4 <- base4cumhaz
rr <- simRecurrent(100,base1,death.cumhaz=dr)
rr$x <- rnorm(nrow(rr)) 
rr$strata <- floor((rr$id-0.01)/50)
drename(rr) <- start+stop~entry+time

ar <- aalen(Surv(start,stop,status)~+1+cluster(id),data=rr,resample.iid=1
                                                     ,max.clust=NULL)
ad <- aalen(Surv(start,stop,death)~+1+cluster(id),data=rr,resample.iid=1,
                                                     ,max.clust=NULL)
mm <- recurrent.marginal.mean(ar,ad)
with(mm,plot(times,mu,type="s"))
with(mm,lines(times,mu+1.96*se.mu,type="s",lty=2))
with(mm,lines(times,mu-1.96*se.mu,type="s",lty=2))
# }