File: bootkm.Rd

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hmisc 4.2-0-1
 1234567891011121314151617181920212223242526272829303132333435363738394041424344454647484950515253545556575859606162636465666768697071727374757677787980 \name{bootkm} \alias{bootkm} \title{ Bootstrap Kaplan-Meier Estimates } \description{ Bootstraps Kaplan-Meier estimate of the probability of survival to at least a fixed time (\code{times} variable) or the estimate of the \code{q} quantile of the survival distribution (e.g., median survival time, the default). } \usage{ bootkm(S, q=0.5, B=500, times, pr=TRUE) } \arguments{ \item{S}{ a \code{Surv} object for possibly right-censored survival time } \item{q}{ quantile of survival time, default is 0.5 for median } \item{B}{ number of bootstrap repetitions (default=500) } \item{times}{ time vector (currently only a scalar is allowed) at which to compute survival estimates. You may specify only one of \code{q} and \code{times}, and if \code{times} is specified \code{q} is ignored. } \item{pr}{ set to \code{FALSE} to suppress printing the iteration number every 10 iterations } } \value{ a vector containing \code{B} bootstrap estimates } \section{Side Effects}{ updates \code{.Random.seed}, and, if \code{pr=TRUE}, prints progress of simulations } \details{ \code{bootkm} uses Therneau's \code{survfitKM} function to efficiently compute Kaplan-Meier estimates. } \author{ Frank Harrell \cr Department of Biostatistics \cr Vanderbilt University School of Medicine \cr \email{f.harrell@vanderbilt.edu} } \references{ Akritas MG (1986): Bootstrapping the Kaplan-Meier estimator. JASA 81:1032--1038. } \seealso{ \code{\link[survival]{survfit}}, \code{\link[survival]{Surv}}, \code{\link[rms]{Survival.cph}}, \code{\link[rms]{Quantile.cph}} } \examples{ # 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 } \keyword{survival} \keyword{nonparametric} \concept{bootstrap}