prev defines a condition's prevalence value
(or baseline probability):
The probability of the condition being TRUE.
prevAn object of class numeric of length 1.
Understanding or obtaining the prevalence value prev:
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).
Consult Wikipedia for additional information.
prob contains current probability information;
num contains basic numeric variables;
init_num initializes basic numeric variables;
comp_prob computes derived probabilities;
comp_freq computes natural frequencies from probabilities;
is_prob verifies probabilities.
Other probabilities:
FDR,
FOR,
NPV,
PPV,
acc,
err,
fart,
mirt,
ppod,
sens,
spec
prev <- .10 # sets a prevalence value of 10%
prev <- 10/100 # (condition = TRUE) for 10 out of 100 individuals
is_prob(prev) # TRUE
#> [1] TRUE