```
# NOT RUN {
# }
# NOT RUN {
###################
## 2 class example
lvs <- c("normal", "abnormal")
truth <- factor(rep(lvs, times = c(86, 258)),
levels = rev(lvs))
pred <- factor(
c(
rep(lvs, times = c(54, 32)),
rep(lvs, times = c(27, 231))),
levels = rev(lvs))
xtab <- table(pred, truth)
sensitivity(pred, truth)
sensitivity(xtab)
posPredValue(pred, truth)
posPredValue(pred, truth, prevalence = 0.25)
specificity(pred, truth)
negPredValue(pred, truth)
negPredValue(xtab)
negPredValue(pred, truth, prevalence = 0.25)
prev <- seq(0.001, .99, length = 20)
npvVals <- ppvVals <- prev * NA
for(i in seq(along = prev))
{
ppvVals[i] <- posPredValue(pred, truth, prevalence = prev[i])
npvVals[i] <- negPredValue(pred, truth, prevalence = prev[i])
}
plot(prev, ppvVals,
ylim = c(0, 1),
type = "l",
ylab = "",
xlab = "Prevalence (i.e. prior)")
points(prev, npvVals, type = "l", col = "red")
abline(h=sensitivity(pred, truth), lty = 2)
abline(h=specificity(pred, truth), lty = 2, col = "red")
legend(.5, .5,
c("ppv", "npv", "sens", "spec"),
col = c("black", "red", "black", "red"),
lty = c(1, 1, 2, 2))
###################
## 3 class example
library(MASS)
fit <- lda(Species ~ ., data = iris)
model <- predict(fit)$class
irisTabs <- table(model, iris$Species)
## When passing factors, an error occurs with more
## than two levels
sensitivity(model, iris$Species)
## When passing a table, more than two levels can
## be used
sensitivity(irisTabs, "versicolor")
specificity(irisTabs, c("setosa", "virginica"))
# }
# NOT RUN {
# }
```

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