km: Kaplan-Meier with robust standard errors

In kkholst/mets: Analysis of Multivariate Event Times

Kaplan-Meier with robust standard errors

Description

Kaplan-Meier with robust standard errors Robust variance is default variance with the summary.

Usage

km(
  formula,
  data = data,
  conf.type = "log",
  conf.int = 0.95,
  robust = TRUE,
  ...
)

Arguments

formula	formula with 'Surv' outcome (see coxph)
data	data frame
conf.type	transformation
conf.int	level of confidence intervals
robust	for robust standard errors based on martingales
...	Additional arguments to lower level funtions

Author(s)

Thomas Scheike

Examples

data(TRACE)
TRACE$cluster <- sample(1:100,1878,replace=TRUE)
out1 <- km(Surv(time,status==9)~strata(vf,chf),data=TRACE)
out2 <- km(Surv(time,status==9)~strata(vf,chf)+cluster(cluster),data=TRACE)

par(mfrow=c(1,2))
bplot(out1,se=TRUE)
bplot(out2,se=TRUE)

kkholst/mets documentation built on April 19, 2024, 7:19 a.m.