R: Plotting predicted survival curves.

plotPredictEventProb {pec} | R Documentation

## Plotting predicted survival curves.

### Description

Ploting time-dependent event risk predictions.

### Usage

    plotPredictEventProb(x, newdata, times, cause = 1, xlim, ylim, xlab,
      ylab, axes = TRUE, col, density, lty, lwd, add = FALSE,
      legend = TRUE, percent = FALSE, ...)

### Arguments

`x` | Object specifying an event risk prediction model.
`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.
`cause` | Show predicted risk of events of this cause
`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 `plotPredictEventProb` 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 http://www.jstatsoft.org/v50/i11/.

### See Also

`predictEventProb` `prodlim`

### Examples

    # generate some competing risk data

[Package pec version 2019.11.03 Index]