PPV defines some decision's positive predictive value (PPV):
The conditional probability of the condition being
provided that the decision is positive.
An object of class
numeric of length 1.
Understanding or obtaining the positive predictive value
PPV is the conditional probability
for the condition being
given a positive decision:
PPV = p(condition = TRUE | decision = positive)
or the probability of a positive decision being correct.
PPV further classifies
the subset of
by condition (
PPV = hi/dec_pos = hi/(hi + fa)).
PPV is the complement of the
false discovery or false detection rate
PPV = 1 - FDR
PPV is the opposite conditional probability
-- but not the complement --
of the sensitivity
sens = p(decision = positive | condition = TRUE)
PPV = hi/dec_pos = hi/(hi + fa)
PPV is a feature of a decision process
or diagnostic procedure and
-- similar to the sensitivity
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
Consult Wikipedia for additional information.
prob contains current probability information;
comp_prob computes current probability information;
num contains basic numeric parameters;
init_num initializes basic numeric parameters;
comp_freq computes current frequency information;
is_prob verifies probabilities.
PPV <- .55 # sets a positive predictive value of 55% PPV <- 55/100 # (condition = TRUE) for 55 out of 100 people with (decision = positive) is_prob(PPV) # TRUE#>  TRUE