Definition: sens is the conditional probability
for a (correct) positive decision given that
the condition is TRUE:
sens = p(decision = positive | condition = TRUE)
or the probability of correctly detecting true cases
(condition = TRUE).
Perspective:
sens further classifies
the subset of cond.true individuals
by decision (sens = hi/cond.true).
Alternative names:
true positive rate (TPR),
hit rate (HR),
probability of detection,
power = 1 - beta,
recall
Relationships:
a. sens is the complement of the miss rate
mirt (aka. false negative rate FNR or the
rate of Type-II errors):
sens = (1 - miss rate) = (1 - FNR)
b. sens is the opposite conditional probability
-- but not the complement --
of the positive predictive value PPV:
PPV = p(condition = TRUE | decision = positive)
In terms of frequencies,
sens is the ratio of
hi divided by
cond.true (i.e., hi + mi):
sens = hi/cond.true = hi/(hi + mi)
Dependencies:
sens is a feature of a decision process
or diagnostic procedure and a measure of
correct decisions (true positives).
Due to being a conditional probability,
the value of sens is not intrinsic to
the decision process, but also depends on the
condition's prevalence value prev.