Step function confidence intervals for ggplot2 — geom

Produces a step function confidence interval for survival curves. This function is taken from the utile.visuals package by Eric Finnesgard. That package is not used because of its strong dependencies.

Usage

geom_stepconfint(
  mapping = NULL,
  data = NULL,
  stat = "identity",
  position = "identity",
  na.rm = FALSE,
  ...
)

Arguments

mapping: Aesthetic mappings with aes() function. Like geom_ribbon(), you must provide columns for x, ymin (lower limit), ymax (upper limit).
data: The data to be displayed in this layer. Can inherit from ggplot parent.
stat: The statistical transformation to use on the data for this layer, as a string. Defaults to 'identity'.
position: Position adjustment, either as a string, or the result of a call to a position adjustment function.
na.rm: If FALSE, the default, missing values are removed with a warning. If TRUE, missing values are silently removed.
...: Optional. Any other ggplot geom_ribbon() arguments.

Note

Originally adapted from the survminer package <https://github.com/kassambara/survminer>.

Author

Eric Finnesgard

Examples

require(survival)
require(ggplot2)
#> Loading required package: ggplot2

f <- survfit(Surv(time, status) ~ trt, data = diabetic)
d <- with(f, data.frame(time, surv, lower, upper, trt=rep(names(f$strata), f$strata)))
ggplot(d, aes(x = time, y=surv)) +
  geom_step(aes(color = trt)) +
  geom_stepconfint(aes(ymin = lower, ymax = upper, fill = trt), alpha = 0.3) +
  coord_cartesian(c(0, 50)) +
  scale_x_continuous(expand = c(0.02,0)) +
  labs(x = 'Time', y = 'Freedom From Event') +
  scale_color_manual(
    values = c('#d83641', '#1A45A7'),
    name = 'Treatment',
    labels = c('None', 'Laser'),
    aesthetics = c('colour', 'fill'))