# Generate some fictional data. Say, 100 individuals take a test with a
# maximum score of 100 and a minimum score of 0.
set.seed(1234)
testdata <- rbinom(100, 100, rBeta.4P(100, 0.25, 0.75, 5, 3))
hist(testdata, xlim = c(0, 100))
# Suppose the cutoff value for attaining a pass is 50 items correct, and
# that the reliability of this test was estimated to 0.7. To calculate the
# necessary (x, y) coordinates to compute the area under the curve statistic
# one can use the LL.ROC() function with the argument
# raw.out = TRUE.
coords <- LL.ROC(x = testdata, reliability = .7, truecut = 50, min = 0,
max = 100, raw.out = TRUE)
# To calculate and retrieve the Area Under the Curve (AUC) with the AUC()
# function, feed it the raw coordinates calculated above.
AUC(coords[, "FPR"], coords[, "TPR"])
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