'surv' Object Confidence Bands Optimized by Area

Given a certain coverage level, obtains simultaneous confidence bands for the survival and cumulative hazard functions such that the area between is minimized. Produces an approximate solution based on local time arguments.

README

This package approaches simultaneous confidence bands for survival functions purely from an optimization perspective: given a certain coverage level, obtain bands such that the area between is minimized. This is achieved through an approximate solution based off local time arguments for both the survival and cumulative-hazard functions.

Installation

install.packages("devtools", repos="http://cran.rstudio.com/")
library(devtools)
devtools::install_github("seasamgo/optband")
library(optband)

Methods

opt.ci(
  survi,              # object of class 'survfit'
  conf.level = 0.95,  # confidence level
  fun = 'surv',       # time-to-event function ('surv' or 'cumhaz')
  tl = NA,            # truncation lower bound
  tu = NA,            # truncation upper bound
  samples = 1         # 1 or 2 sample case
  )

opt.ci takes a survfit object from the survival package as input and returns a survfit object with confidence bands for the specified time-to-event function (e.g. the two-sample cumulative hazard difference function). Additional optional parameters include the confidence level 1 − α, optional upper or lower bounds for data truncation, and the number of samples to consider (1 or 2).

Please view the corresponding help files for more.

Example

Obtain minimal-area confidence bands for bladder cancer data from the survival package:

library(survival)

## 1-sample case
dat <- bladder[bladder$enum==1,]
s <- survival::survfit(Surv(stop, event) ~ 1, type = "kaplan-meier", data = dat)
optband_s <- optband::opt.ci(s)
plot(optband_s, xlab = "time", ylab = "KM curve", mark.time = FALSE)