R: Plots for Competing Risks

plot.competing.risk {randomForestSRC} | R Documentation

## Plots for Competing Risks

### Description

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. 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.

### 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)
      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))
    }

[Package randomForestSRC version 2.7.0 Index]