Plot the ensemble cumulative incidence function (CIF) and
cause-specific cumulative hazard function (CSCHF) from a competing risk
analysis.
Usage
## S3 method for class 'rfsrc'
plot.competing.risk(x, plots.one.page = FALSE, ...)
Arguments
x
An object of class (rfsrc, grow) or
(rfsrc, predict).
plots.one.page
Should plots be placed on one page?
...
Further arguments passed to or from other methods.
Details
Ensemble ensemble CSCHF and CIF functions for each event type.
Does not apply to right-censored data.
Author(s)
Hemant Ishwaran and Udaya B. Kogalur
References
Ishwaran H., Gerds T.A., Kogalur U.B., Moore R.D., Gange S.J. and Lau
B.M. (2014). Random survival forests for competing risks.
Biostatistics, 15(4):757-773.
See Also
follic,
hd,
rfsrc,
wihs
Examples
## Not run:
## ------------------------------------------------------------
## follicular cell lymphoma
## ------------------------------------------------------------
data(follic, package = "randomForestSRC")
follic.obj <- rfsrc(Surv(time, status) ~ ., follic, nsplit = 3, ntree = 100)
plot.competing.risk(follic.obj)
## ------------------------------------------------------------
## competing risk analysis of pbc data from the survival package
## events are transplant (1) and death (2)
## ------------------------------------------------------------
if (library("survival", logical.return = TRUE)) {
data(pbc, package = "survival")
pbc$id <- NULL
plot.competing.risk(rfsrc(Surv(time, status) ~ ., pbc, nsplit = 10))
}
## End(Not run)