The ROC curve compares the rank of prediction and answer. Therefore, you could evaluate the ROC curve with package pROC
as follow:
mydata <- read.csv("http://www.ats.ucla.edu/stat/data/binary.csv")
mylogit <- glm(admit ~ gre, data = mydata, family = "binomial")
summary(mylogit)
prob=predict(mylogit,type=c("response"))
mydata$prob=prob
library(pROC)
g <- roc(admit ~ prob, data = mydata)
plot(g)