Definition:
prev is the (non-conditional) probability:
prev = p(condition = TRUE)
or the base rate (or baseline probability)
of the condition's occurrence or truth.
In terms of frequencies,
prev is the ratio of
cond_true (i.e., hi + mi)
divided by N (i.e.,
hi + mi + fa + cr):
prev = cond_true/N = (hi + mi)/(hi + mi + fa + cr)
Perspective:
prev classifies a population of N individuals
by condition (prev = cond_true/N).
prev is the "by condition" counterpart
to ppod (when adopting a "by decision" perspective) and
to acc (when adopting a "by accuracy" perspective).
Alternative names:
base rate of condition,
proportion affected,
rate of condition = TRUE cases.
prev is often distinguished from the incidence rate
(i.e., the rate of new cases within a certain time period).
Dependencies:
prev is a feature of the population
and of the condition, but independent of the decision process
or diagnostic procedure.
While the value of prev does not depend
on features of the decision process or diagnostic procedure,
prev must be taken into account when
computing the conditional probabilities
sens, mirt,
spec, fart,
PPV, and NPV
(as they depend on prev).