R: Plotting predicted survival curves.

plotPredictSurvProb {pec} | R Documentation

## Plotting predicted survival curves.

### Description

Ploting prediction survival curves for one prediction model using `predictSurvProb` .

### Usage

    plotPredictSurvProb(
      x,
      newdata,
      times,
      xlim,
      ylim,
      xlab,
      ylab,
      axes = TRUE,
      col,
      density,
      lty,
      lwd,
      add = FALSE,
      legend = TRUE,
      percent = FALSE,
      ...
    )

### Arguments

`x` | A survival prediction model including `call` and `formula` object.
`newdata` | A data frame with the same variable names as those that were used to fit the model `x`.
`times` | Vector of times at which to return the estimated probabilities.
`xlim` | Plotting range on the x-axis.
`ylim` | Plotting range on the y-axis.
`xlab` | Label given to the x-axis.
`ylab` | Label given to the y-axis.
`axes` | Logical. If `FALSE` no axes are drawn.
`col` | Vector of colors given to the survival curve.
`density` | Densitiy of the color – useful for showing many (overlapping) curves.
`lty` | Vector of lty's given to the survival curve.
`lwd` | Vector of lwd's given to the survival curve.
`add` | Logical. If `TRUE` only lines are added to an existing device
`legend` | Logical. If TRUE a legend is plotted by calling the function legend. Optional arguments of the function `legend` can be given in the form `legend.x=val` where x is the name of the argument and val the desired value. See also Details.
`percent` | Logical. If `TRUE` the y-axis is labeled in percent.
`...` | Parameters that are filtered by `SmartControl` and then passed to the functions: `plot`, `axis`, `legend`.

### Details

Arguments for the invoked functions `legend` and `axis` are simply specified as `legend.lty=2`. The specification is not case sensitive, thus `Legend.lty=2` or `LEGEND.lty=2` will have the same effect. The function `axis` is called twice, and arguments of the form `axis1.labels`, `axis1.at` are used for the time axis whereas `axis2.pos`, `axis1.labels`, etc. are used for the y-axis.

These arguments are processed via `...{}` of `plotPredictSurvProb` and inside by using the function `SmartControl`.

### Value

The (invisible) object.

### Author(s)

Ulla B. Mogensen ulmo@biostat.ku.dk, Thomas A. Gerds tag@biostat.ku.dk

### References

Ulla B. Mogensen, Hemant Ishwaran, Thomas A. Gerds (2012). Evaluating Random Forests for Survival Analysis Using Prediction Error Curves. Journal of Statistical Software, 50(11), 1-23. URL https://www.jstatsoft.org/v50/i11.

### See Also

`predictSurvProb` `prodlim`

### Examples

    # generate some survival data
    library(prodlim)
    d <- SimSurv(100)
    # then fit a Cox model
    library(rms)
    coxmodel <- cph(Surv(time,status)~X1+X2,data=d,surv=TRUE)
    # plot predicted survival probabilities for all time points
    ttt <- sort(unique(d$time))
    # and for selected predictor values:
     ndat <- data.frame(X1=c(0.25,0.25,-0.05,0.05),X2=c(0,1,0,1))
    plotPredictSurvProb(coxmodel,newdata=ndat,times=ttt)

    # the same can be done e.g. for a randomSurvivalForest model
    library(randomForestSRC)
    rsfmodel <- rfsrc(Surv(time,status)~X1+X2,data=d)
    plotPredictSurvProb(rsfmodel,newdata=ndat,times=ttt)

[Package pec version 2020.11.17 Index]