sensitivity: Sensitivity
In frankchien/bmi585flc: BMI 585 Final- Biostatistical Functions.

Description Usage Arguments Details Value Examples

Computes sensitivity given set of predictions and set of ground truths

1	sensitivity(pred, truth)

`pred`	vector of 1s and 0s or True and False representing predictions
`truth`	vector of 1s and 0s or True and False representing gold standards or ground truths

Takes in vectors representing a prediction and a ground truth. Vectors may be either logical using T/F or numeric using 1 and 0s. Vectors must be of the same length

sensitivity given as true pos/(true pos + false neg)

pred1 <- c(1,1,0,1,1,0,0)
truth1 < c(1,0,0,1,1,0,1)
sensitivity(pred1,truth1)

pred2 <- c(T,T,F,T,T,F,F)
truth2 <- c(T,F,F,T,T,F,T)
sensitivity(pred2, truth2)