summary.cor: Summary for dependence models for competing risks

In mets: Analysis of Multivariate Event Times

Summary for dependence models for competing risks

Description

Computes concordance and casewise concordance for dependence models for competing risks models of the type cor.cif, rr.cif or or.cif for the given cumulative incidences and the different dependence measures in the object.

Usage

## S3 method for class 'cor'
summary(object, marg.cif = NULL, marg.cif2 = NULL, digits = 3, ...)

Arguments

object	object from cor.cif rr.cif or or.cif for dependence between competing risks data for two causes.
marg.cif	a number that gives the cumulative incidence in one time point for which concordance and casewise concordance are computed.
marg.cif2	the cumulative incidence for cause 2 for concordance and casewise concordance are computed. Default is that it is the same as marg.cif.
digits	digits in output.
...	Additional arguments.

Value

prints summary for dependence model.

casewise	gives casewise concordance that is, probability of cause 2 (related to cif2) given that cause 1 (related to cif1) has occured.
concordance	gives concordance that is, probability of cause 2 (related to cif2) and cause 1 (related to cif1).
cif1	cumulative incidence for cause1.
cif2	cumulative incidence for cause1.

Author(s)

Thomas Scheike

References

Cross odds ratio Modelling of dependence for Multivariate Competing Risks Data, Scheike and Sun (2012), Biostatistics.

A Semiparametric Random Effects Model for Multivariate Competing Risks Data, Scheike, Zhang, Sun, Jensen (2010), Biometrika.

Examples

## library("timereg")
## data("multcif",package="mets") # simulated data 
## multcif$cause[multcif$cause==0] <- 2
##  
## times=seq(0.1,3,by=0.1) # to speed up computations use only these time-points
## add <- timereg::comp.risk(Event(time,cause)~+1+cluster(id),
##                           data=multcif,n.sim=0,times=times,cause=1)
###
## out1<-cor.cif(add,data=multcif,cause1=1,cause2=1,theta=log(2+1))
## summary(out1)
## 
## pad <- predict(add,X=1,se=0,uniform=0)
## summary(out1,marg.cif=pad)

mets documentation built on May 29, 2024, 3:51 a.m.