times
variable) or the estimate of the
q
quantile of the survival distribution (e.g., median survival time, the
default).
bootkm(S, q=0.5, B=500, times, pr=TRUE)
Surv
object for possibly right-censored survival time
q
and
times
, and
if
times
is specified
q
is ignored.
FALSE
to suppress printing the iteration number every 10 iterations
bootkm
uses Therneau's
survfit.km
function to efficiently compute
Kaplan-Meier estimates.
B
bootstrap estimates
Frank Harrell
Department of Biostatistics
Vanderbilt University School of Medicine
f.harrell@vanderbilt.edu
Akritas MG (1986): Bootstrapping the Kaplan-Meier estimator. JASA 81:1032–1038.
# Compute 0.95 nonparametric confidence interval for the difference in # median survival time between females and males (two-sample problem) set.seed(1) library(survival) S <- Surv(runif(200)) # no censoring sex <- c(rep('female',100),rep('male',100)) med.female <- bootkm(S[sex=='female',], B=100) # normally B=500 med.male <- bootkm(S[sex=='male',], B=100) describe(med.female-med.male) quantile(med.female-med.male, c(.025,.975), na.rm=TRUE) # na.rm needed because some bootstrap estimates of median survival # time may be missing when a bootstrap sample did not include the # longer survival times