# Incident/Dynamic (I/D) ROC curve, AUC and integrated AUC (iAUC) estimation of censored survival data

### Description

This function creates Kaplan-Meier plot.

### Usage

1 |

### Arguments

`Stime` |
unique ordered event times |

`survival` |
estimates of survival probabilities at |

`max.T` |
maximum time to be considered for plotting, default is NULL which plots survival till max(Stime)+1 units |

`lty` |
line type |

`all` |
TRUE or FALSE, default is TRUE |

`...` |
additional plot arguments |

### Details

This function creates Kaplan-Meier plot. If *all=TRUE*, then this
creates a new plot. If *all=FALSE*, it adds line to an existing plot and
hence must be called after a plot() or similar call.

### Author(s)

Patrick J. Heagerty

### References

Heagerty, P.J., Zheng Y. (2005)
Survival Model Predictive Accuracy and ROC curves
*Biometrics*, **61**, 92 – 105

### Examples

1 2 3 4 5 6 7 8 | ```
data(pbc)
## considering only randomized patients
pbc1 <- pbc[1:312,]
## create new censoring variable combine 0,1 as 0, 2 as 1
survival.status <- ifelse( pbc1$status==2, 1, 0)
survival.time <- pbc1$fudays
kout <- weightedKM(Stime=survival.time, status=survival.status)
KM.plot(kout$time,kout$survival)
``` |

Want to suggest features or report bugs for rdrr.io? Use the GitHub issue tracker. Vote for new features on Trello.