R: Estimates marginal mean of recurrent events

recurrent.marginal.mean {timereg} | R Documentation

## 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.

### Author(s)

Thomas Scheike

### References

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

### Examples

    ### 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))

[Package timereg version 1.9.4 Index]