km {mets}

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)