plot.competing.risk.rfsrc: Plots for Competing Risks

In randomForestSRC: Fast Unified Random Forests for Survival, Regression, and Classification (RF-SRC)

Plots for Competing Risks

Description

Plot useful summary curves from a random survival forest 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

Given a random survival forest object from a competing risk analysis (Ishwaran et al. 2014), plots from top to bottom, left to right: (1) cause-specific cumulative hazard function (CSCHF) for each event, (2) cumulative incidence function (CIF) for each event, and (3) continuous probability curves (CPC) for each event (Pepe and Mori, 1993).

Does not apply to right-censored data. Whenever possible, out-of-bag (OOB) values are displayed.

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.

Pepe, M.S. and Mori, M., (1993). Kaplan-Meier, marginal or conditional probability curves in summarizing competing risks failure time data? Statistics in Medicine, 12(8):737-751.

See Also

follic, hd, rfsrc, wihs

Examples

## ------------------------------------------------------------
## follicular cell lymphoma
## ------------------------------------------------------------

  data(follic, package = "randomForestSRC")
  follic.obj <- rfsrc(Surv(time, status) ~ ., follic, nsplit = 3, ntree = 100)
  print(follic.obj)
  plot.competing.risk(follic.obj)

## ------------------------------------------------------------
## Hodgkin's Disease
## ------------------------------------------------------------

  data(hd, package = "randomForestSRC")
  hd.obj <- rfsrc(Surv(time, status) ~ ., hd, nsplit = 3, ntree = 100)
  print(hd.obj)
  plot.competing.risk(hd.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))
}

randomForestSRC documentation built on Sept. 11, 2024, 7:50 p.m.