R: Estimates the casewise concordance based on Concordance and...
casewise.test
R Documentation
Estimates the casewise concordance based on Concordance and marginal estimate using timereg and performs test for independence
Description
Estimates the casewise concordance based on Concordance and marginal estimate using timereg and performs test for independence
Usage
casewise.test(conc, marg, test = "no-test", p = 0.01)
Arguments
conc
Concordance
marg
Marginal estimate
test
Type of test for independence assumption. "conc" makes test on concordance scale and "case" means a test on the casewise concordance
p
check that marginal probability is greater at some point than p
Details
Uses cluster based conservative standard errors for marginal
Author(s)
Thomas Scheike
Examples
## Reduce Ex.Timings
data(prt);
prt <- prt[which(prt$id %in% sample(unique(prt$id),7500)),]
### marginal cumulative incidence of prostate cancer
times <- seq(60,100,by=2)
outm <- comp.risk(Event(time,status)~+1,data=prt,cause=2,times=times)
cifmz <- predict(outm,X=1,uniform=0,resample.iid=1)
cifdz <- predict(outm,X=1,uniform=0,resample.iid=1)
### concordance for MZ and DZ twins
cc <- bicomprisk(Event(time,status)~strata(zyg)+id(id),
data=prt,cause=c(2,2))
cdz <- cc$model$"DZ"
cmz <- cc$model$"MZ"
### To compute casewise cluster argument must be passed on,
### here with a max of 100 to limit comp-time
outm <-comp.risk(Event(time,status)~+1,data=prt,
cause=2,times=times,max.clust=100)
cifmz <-predict(outm,X=1,uniform=0,resample.iid=1)
cc <-bicomprisk(Event(time,status)~strata(zyg)+id(id),data=prt,
cause=c(2,2),se.clusters=outm$clusters)
cdz <- cc$model$"DZ"
cmz <- cc$model$"MZ"
cdz <- casewise.test(cdz,cifmz,test="case") ## test based on casewise
cmz <- casewise.test(cmz,cifmz,test="conc") ## based on concordance
plot(cmz,ylim=c(0,0.7),xlim=c(60,100))
par(new=TRUE)
plot(cdz,ylim=c(0,0.7),xlim=c(60,100))
slope.process(cdz$casewise[,1],cdz$casewise[,2],iid=cdz$casewise.iid)
slope.process(cmz$casewise[,1],cmz$casewise[,2],iid=cmz$casewise.iid)