stat_km: Adds a Kaplan Meier Estimate of Survival

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Adds a Kaplan Meier Estimate of Survival

Description

Adds a Kaplan Meier Estimate of Survival

Usage

stat_km(
  mapping = NULL,
  data = NULL,
  geom = "km",
  position = "identity",
  show.legend = NA,
  inherit.aes = TRUE,
  trans = scales::identity_trans(),
  firstx = 0,
  firsty = 1,
  type = "kaplan-meier",
  start.time = 0,
  ...
)

Arguments

mapping	Set of aesthetic mappings created by aes(). If specified and inherit.aes = TRUE (the default), it is combined with the default mapping at the top level of the plot. You must supply mapping if there is no plot mapping.
data	The data to be displayed in this layer. There are three options: If NULL, the default, the data is inherited from the plot data as specified in the call to ggplot(). A data.frame, or other object, will override the plot data. All objects will be fortified to produce a data frame. See fortify() for which variables will be created. A function will be called with a single argument, the plot data. The return value must be a data.frame, and will be used as the layer data. A function can be created from a formula (e.g. ~ head(.x, 10)).
geom	The geometric object to use to display the data, either as a ggproto Geom subclass or as a string naming the geom stripped of the geom_ prefix (e.g. "point" rather than "geom_point")
position	Position adjustment, either as a string naming the adjustment (e.g. "jitter" to use position_jitter), or the result of a call to a position adjustment function. Use the latter if you need to change the settings of the adjustment.
show.legend	logical. Should this layer be included in the legends? NA, the default, includes if any aesthetics are mapped. FALSE never includes, and TRUE always includes. It can also be a named logical vector to finely select the aesthetics to display.
inherit.aes	If FALSE, overrides the default aesthetics, rather than combining with them. This is most useful for helper functions that define both data and aesthetics and shouldn't inherit behaviour from the default plot specification, e.g. borders().
trans	Transformation to apply to the survival probabilities. Defaults to "identity". Other options include "event", "cumhaz", "cloglog", or define your own using trans_new.
firstx, firsty	the starting point for the survival curves. By default, the plot program obeys tradition by having the plot start at (0,1).
type	an older argument that combined stype and ctype, now deprecated. Legal values were "kaplan-meier" which is equivalent to stype=1, ctype=1, "fleming-harrington" which is equivalent to stype=2, ctype=1, and "fh2" which is equivalent to stype=2, ctype=2.
start.time	numeric value specifying a time to start calculating survival information. The resulting curve is the survival conditional on surviving to start.time.
...	Other arguments passed to survfit.formula

Details

This stat is for computing the confidence intervals for the Kaplan-Meier survival estimate for right-censored data. It requires the aesthetic mapping x for the observation times and status which indicates the event status, 0=alive, 1=dead or 1/2 (2=death). Logical status is not supported.

Value

a data.frame with additional columns:

x	x in data
y	Kaplan-Meier Survival Estimate at x

Aesthetics

stat_km understands the following aesthetics (required aesthetics are in bold):

• time The survival times

• status The censoring indicator, see Surv for more information.

• alpha

• color

• linetype

• size

Examples

library(ggplot2)
sex <- rbinom(250, 1, .5)
df <- data.frame(time = exp(rnorm(250, mean = sex)), status = rbinom(250, 1, .75), sex = sex)
ggplot(df, aes(time = time, status = status, color = factor(sex))) +
 stat_km()

## Examples illustrating the options passed to survfit.formula

p1 <- ggplot(df, aes(time = time, status = status))
p1 + stat_km()
p1 + stat_km(trans = "cumhaz")
# for cloglog plots also log transform the time axis
p1 + stat_km(trans = "cloglog") + scale_x_log10()
p1 + stat_km(type = "fleming-harrington")
p1 + stat_km(start.time = 5)

ggquickeda documentation built on April 1, 2023, 12:10 a.m.