| plot.competing.risk {randomForestSRC} | R Documentation |
Plot the ensemble cumulative incidence function (CIF) and cause-specific cumulative hazard function (CSCHF) from a competing risk analysis.
## S3 method for class 'rfsrc' plot.competing.risk(x, plots.one.page = FALSE, ...)
x |
An object of class |
plots.one.page |
Should plots be placed on one page? |
... |
Further arguments passed to or from other methods. |
Ensemble ensemble CSCHF and CIF functions for each event type. Does not apply to right-censored data. Whenever possible, out-of-bag (OOB) values are displayed.
Hemant Ishwaran and Udaya B. Kogalur
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.
## ------------------------------------------------------------
## 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))
}