gg_survival {ggRandomForests} | R Documentation |
Nonparametric survival estimates.
Description
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. |
Details
gg_survival
is a wrapper function for generating
nonparametric survival estimates using either nelson
-Aalen
or kaplan
-Meier estimates.
Value
A gg_survival
object created using the non-parametric
Kaplan-Meier or Nelson-Aalen estimators.
See Also
Examples
## Not run:
## -------- 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")
## End(Not run)
[Package ggRandomForests version 2.2.1 Index]