Plot the ensemble cumulative incidence function (CIF) and cause-specific cumulative hazard function (CSCHF) from a competing risk analysis.
# S3 method for rfsrc
plot.competing.risk(x, plots.one.page = FALSE, ...)
An object of class (rfsrc, grow)
or
(rfsrc, predict)
.
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.
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.
# 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))
}
# }
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