mirt defines a decision's miss rate value:
The conditional probability of the decision being negative
if the condition is TRUE.
mirtAn object of class numeric of length 1.
Understanding or obtaining the miss rate mirt:
Definition: sens is the conditional probability
for an incorrect negative decision given that
the condition is TRUE:
mirt = p(decision = negative | condition = TRUE)
or the probability of failing to detect true cases
(condition = TRUE).
Perspective:
mirt further classifies
the subset of cond_true individuals
by decision (mirt = mi/cond_true).
Alternative names:
false negative rate (FNR),
rate of type-II errors (beta)
Relationships:
a. mirt is the complement of the
sensitivity sens (aka. hit rate HR):
mirt = (1 - sens) = (1 - HR)
b. mirt is the _opposite_ conditional probability
-- but not the complement --
of the false omission rate FOR:
FOR = p(condition = TRUE | decision = negative)
In terms of frequencies,
mirt is the ratio of
mi divided by cond_true
(i.e., hi + mi):
mirt = mi/cond_true = mi/(hi + mi)
Dependencies:
mirt is a feature of a decision process
or diagnostic procedure and a measure of
incorrect decisions (false negatives).
However, due to being a conditional probability,
the value of mirt is not intrinsic to
the decision process, but also depends on the
condition's prevalence value prev.
Consult Wikipedia for additional information.
comp_mirt computes mirt as the complement of sens;
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.
Other probabilities:
FDR,
FOR,
NPV,
PPV,
acc,
err,
fart,
ppod,
prev,
sens,
spec
mirt <- .15 # => sets a miss rate of 15%
mirt <- 15/100 # => (decision = negative) for 15 out of 100 people with (condition = TRUE)