Nonparametric survival estimates.

Usage

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

Arguments

interval: name of the interval variable in the training dataset.
censor: name of the censoring variable in the training dataset.
by: stratifying variable in the training dataset, defaults to NULL
data: name of the training data.frame
type: one of ("kaplan","nelson"), defaults to Kaplan-Meier
...: extra arguments passed to Kaplan or Nelson functions.

Value

A gg_survival object created using the non-parametric Kaplan-Meier or Nelson-Aalen estimators.

Details

gg_survival is a wrapper function for generating nonparametric survival estimates using either nelson-Aalen or kaplan-Meier estimates.

Examples

## -------- pbc data
data(pbc, package = "randomForestSRC")
pbc$time <- pbc$days / 364.25

# This is the same as kaplan
gg_dta <- gg_survival(
  interval = "time", censor = "status",
  data = pbc
)

plot(gg_dta, error = "none")

plot(gg_dta)


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

plot(gg_dta, error = "none")

plot(gg_dta)


# ...with smaller confidence limits.
gg_dta <- gg_survival(
  interval = "time", censor = "status",
  data = pbc, by = "treatment", conf.int = .68
)

plot(gg_dta, error = "lines")