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prev
defines a condition's prevalence value
(or baseline probability):
The probability of the condition being TRUE
.
prev
An 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
Other essential parameters:
cr
,
fa
,
hi
,
mi
,
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
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