Compute the points for an ROC curve
Computes sensitivity and specificity for a variety of cutoffs
roc(data, class, dataGrid = TRUE, gridLength = 100, positive = levels(class))
- a numeric variable to cut along
- a factor with class memberships. There must be only two classes.
- should the data define the grid of cut-points? If not a sequence of evenly spaced intervals is used.
- number of intervals to use if the data do not define the grid.
- a character string for the level of the class variable that defines a "positive" event
- A matrix of results with columns "cutoff", "sensitivity" and "specificity"
The first row in the output has a cutoff of
NA, zero specificity and sensitivity of one.
set.seed(6) testData <- data.frame(x = c(rnorm(200), rnorm(200) + 1), group = factor(rep(letters[1:2], each = 200))) densityplot(~testData$x, groups = testData$group, auto.key = TRUE) roc(testData$x, testData$group)
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