Create a Kaplan-Meier plot using ggplot2

Usage

km_ggplot(
  sfit,
  xlabs = "Time",
  ylabs = "",
  strata_labs = NULL,
  ystratalabs = deprecated(),
  timeby = NULL,
  pval = FALSE,
  p_digits = getOption("cctu_p_digits", default = 4),
  ...
)

Arguments

sfit: a survfit object
xlabs: x-axis label
ylabs: y-axis label
strata_labs: The strata labels. If left as NULL it defaults to levels(summary(sfit)$strata) with minor prettification.
ystratalabs: deprecated and only for back compatibility. use strata_labs argument.
timeby: numeric: Default is NULL to use ggplot defaults, but allows user to specify the gaps between x-axis ticks
pval: logical: add the p-value to the plot?
p_digits: integer: the number of decimal places to use for a p-value.
...: option parameters include `xlims` and `ylims` to set the axes' ranges, where defaults are derived from the data: both are vectors of length two giving the min and max.

Value

a list of ggplot objects is made: the top figure and a table of counts. The object has a print and plot method that uses wrap_plots to glue together. The user can access and modify the ggplot components as desired.

Details

This function will return a list of `ggplot2` object. The KM-plot will stored at `top` and risktable will stored at `bottom`. You can modifies those as you normally draw a plot with `ggplot2`. You can modify anything you want except the x-axis scale of the plot, otherwise the x-axis of KM-plot and the risk table will not align. There are other packages, like `ggsurvfit`, you can use to draw a KM-plot with more options.

Author

Original taken from http://statbandit.wordpress.com/2011/03/08/an-enhanced-kaplan-meier-plot/ but modified by authors of cctu package.

Examples

library(survival)
fit <- survfit(Surv(time, status) ~ rx, data = colon)
km_ggplot(fit)

## Change theme of the KM-plot
p <- km_ggplot(fit)
p$top <- p$top +
  ggplot2::theme_classic()
# Change the theme of the risktable
p$bottom <- p$bottom +
  ggplot2::theme_void()

plot(p)