Nonparametric survival estimates.

Usage

gg_survival(
  object = NULL,
  interval = NULL,
  censor = NULL,
  by = NULL,
  data = NULL,
  type = c("kaplan", "nelson"),
  ...
)

# S3 method for class 'rfsrc'
gg_survival(
  object,
  interval = NULL,
  censor = NULL,
  by = NULL,
  data = NULL,
  type = c("kaplan", "nelson"),
  ...
)

# Default S3 method
gg_survival(
  object = NULL,
  interval = NULL,
  censor = NULL,
  by = NULL,
  data = NULL,
  type = c("kaplan", "nelson"),
  ...
)

Arguments

object: For the rfsrc method: a fitted rfsrc survival forest. For the default method: pass NULL (or omit) and supply interval, censor, and data instead.
interval: Character; name of the time-to-event column in data (default method only).
censor: Character; name of the event-indicator column in data (1 = event, 0 = censored; default method only).
by: Optional character; name of a grouping column for stratified estimates. For the rfsrc method, by must be a column in object$xvar.
data: A data.frame containing survival data (default method only).
type: One of "kaplan" (Kaplan-Meier, default) or "nelson" (Nelson-Aalen cumulative hazard). Default method only.
...: Additional arguments passed to kaplan or nelson.

Value

A gg_survival data.frame with columns time, surv, cum_haz, lower, upper, n.risk, and optionally groups when by is supplied.

Details

gg_survival is an S3 generic for generating nonparametric survival estimates. It dispatches on the class of its first argument:

rfsrc: Extracts the response data from the fitted forest and delegates to kaplan. Use the by argument to stratify on a predictor stored in the model's xvar slot.
default: Accepts raw survival data columns via the interval, censor, by, and data arguments, delegating to either kaplan (default) or nelson.

Examples

## -------- pbc data (default method — raw data columns)
data(pbc, package = "randomForestSRC")
pbc$time <- pbc$days / 364.25

gg_dta <- gg_survival(interval = "time", censor = "status", data = pbc)
plot(gg_dta, error = "none")


# Stratified
gg_dta <- gg_survival(
  interval = "time", censor = "status",
  data = pbc, by = "treatment"
)
plot(gg_dta)