plotROC: Plot ROC curves

In riskRegression: Risk Regression Models and Prediction Scores for Survival Analysis with Competing Risks

Plot ROC curves

Description

Plot ROC curve

Usage

plotROC(
  x,
  models,
  times,
  xlab = "1-Specificity",
  ylab = "Sensitivity",
  col,
  lwd,
  lty = 1,
  cex = 1,
  pch = 1,
  legend = !add,
  auc.in.legend = TRUE,
  brier.in.legend = FALSE,
  add = FALSE,
  ...
)

Arguments

x	Object obtained with function Score
models	Choice of models to plot
times	Time point(s) specifying the prediction horizon
xlab	Label for x-axis
ylab	Label for y-axis
col	line color
lwd	line width
lty	line style
cex	point size
pch	point style
legend	logical. If 1L draw a legend with the values of AUC.
auc.in.legend	Logical. If TRUE add AUC to legend.
brier.in.legend	Logical. If TRUE add Brier score to legend.
add	logical. If 1L add lines to an existing plot.
...	Used for additional control of the subroutines: plot, axis, lines, legend, addtable2plot. See SmartControl.

Examples

## binary
set.seed(18)
if (require("randomForest",quietly=TRUE)){
library(randomForest)
library(prodlim)
bdl <- sampleData(40,outcome="binary")
bdt <- sampleData(58,outcome="binary")
bdl[,y:=factor(Y)]
bdt[,y:=factor(Y)]
fb1 <- glm(y~X1+X2+X3+X4+X5+X6+X7+X8+X9+X10,data=bdl,family="binomial")
fb2 <- randomForest(y~X1+X2+X3+X4+X5+X6+X7+X8+X9+X10,data=bdl)
xb <- Score(list("glm"=fb1,"rf"=fb2),y~1,data=bdt,
            plots="roc",metrics=c("auc","brier"))
plotROC(xb,brier.in.legend=1L)

# with cross-validation
## Not run: 
xb3 <- Score(list("glm"=fb1,"rf"=fb2),y~1,data=bdl,
            plots="roc",B=3,split.method="bootcv",
            metrics=c("auc"))

## End(Not run)
}
## survival
set.seed(18)
library(survival)
sdl <- sampleData(40,outcome="survival")
sdt <- sampleData(58,outcome="survival")
fs1 <- coxph(Surv(time,event)~X3+X5+X6+X7+X8+X10,data=sdl,x=TRUE)
fs2 <- coxph(Surv(time,event)~X1+X2+X9,data=sdl,x=TRUE)
xs <- Score(list(model1=fs1,model2=fs2),Hist(time,event)~1,data=sdt,
            times=5,plots="roc",metrics="auc")
plotROC(xs)
## competing risks
data(Melanoma)
f1 <- CSC(Hist(time,status)~age+sex+epicel+ulcer,data=Melanoma)
f2 <- CSC(Hist(time,status)~age+sex+logthick+epicel+ulcer,data=Melanoma)
x <- Score(list(model1=f1,model2=f2),Hist(time,status)~1,data=Melanoma,
            cause=1,times=5*365.25,plots="roc",metrics="auc")
plotROC(x)

riskRegression documentation built on Sept. 8, 2023, 6:12 p.m.