Definition:
PPV
is the conditional probability
for the condition being TRUE
given a positive decision:
PPV = p(condition = TRUE | decision = positive)
or the probability of a positive decision being correct.
Perspective:
PPV
further classifies
the subset of dec.pos
individuals
by condition (PPV = hi/dec.pos = hi/(hi + fa)
).
Alternative names:
precision
Relationships:
a. PPV
is the complement of the
false discovery or false detection rate FDR
:
PPV = 1 - FDR
b. PPV
is the opposite conditional probability
-- but not the complement --
of the sensitivity sens
:
sens = p(decision = positive | condition = TRUE)
In terms of frequencies,
PPV
is the ratio of
hi
divided by dec.pos
(i.e., hi + fa
):
PPV = hi/dec.pos = hi/(hi + fa)
Dependencies:
PPV
is a feature of a decision process
or diagnostic procedure and
-- similar to the sensitivity sens
--
a measure of correct decisions (positive decisions
that are actually TRUE).
However, due to being a conditional probability,
the value of PPV
is not intrinsic to
the decision process, but also depends on the
condition's prevalence value prev
.