plot.tdROC: Plot the time-dependent ROC curve

In tdROC: Nonparametric Estimation of Time-Dependent ROC Curve from Right Censored Survival Data

Description

Plot the ROC curve estimated by tdROC().

Usage

## S3 method for class 'tdROC'
plot(x, lwd = 2, xlab = "1-specificity",
  ylab = "sensitivity", xlim = c(0, 1), ylim = c(0, 1), col = "black",
  main = "ROC curve", abline = T, ...)

Arguments

x	the object returned by tdROC().
lwd	user-specified line width. Default is 2.
xlab	user-specified label for x-axis. Default is "1-specificity".
ylab	user-specified label for y-axis. Default is "sensitivity".
xlim	user-specified limit for x axis. Default is c(0,1).
ylim	user-specified limit for y axis. Default is c(0,1).
col	user-specified color for ROC curve. Defualt is "black".
main	user-specified title for the plot. Default is "ROC curve"
abline	user-specified reference diagnol line. Default is True.
...	for future methods

Value

Returns a plot of ROC curve.

Examples

library( survival )
data( mayo );
dat <- mayo[ , c( "time","censor","mayoscore5" )] ;
fm <- tdROC( X = dat$mayoscore5, Y = dat$time, delta = dat$censor,
             tau = 365*6, span = 0.1, nboot = 0, alpha = 0.05, n.grid = 1000, cut.off = 5:9 )
# plot the object "fm" from tdR0C()
plot.tdROC( fm ) ;

tdROC documentation built on May 2, 2019, 8:31 a.m.