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

Description

This function creates Kaplan-Meier plot.

Usage

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KM.plot(Stime, survival, max.T=NULL, lty=NULL, all=TRUE, ...) 

Arguments

Stime

unique ordered event times

survival

estimates of survival probabilities at Stime

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

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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)