Produces a step function confidence interval for survival curves.
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.
Examples
library(survival)
library(ggplot2)
fit <- survfit(Surv(time, status) ~ trt, data = diabetic)
fit <- survfit0(fit) # connect origin
ggplot(
data = data.frame(
time = fit$time,
surv = fit$surv,
conf.low = fit$lower,
conf.high = fit$upper,
strata = rep(names(fit$strata), fit$strata)
),
mapping = aes(x = time, y = surv)
) +
geom_step(aes(color = strata)) +
geom_stepconfint(aes(ymin = conf.low, ymax = conf.high, fill = strata), 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')) +
theme_basic()