mirt defines a decision's miss rate value:
The conditional probability of the decision being negative
if the condition is
An object of class
numeric of length 1.
Understanding or obtaining the miss rate
sens is the conditional probability
for an incorrect negative decision given that
the condition is
mirt = p(decision = negative | condition = TRUE)
or the probability of failing to detect true cases
condition = TRUE).
mirt further classifies
the subset of
by decision (
mirt = mi/cond_true).
false negative rate (
rate of type-II errors (
mirt is the complement of the
sens (aka. hit rate
mirt = (1 - sens) = (1 - HR)
mirt is the _opposite_ conditional probability
-- but not the complement --
of the false omission rate
FOR = p(condition = TRUE | decision = negative)
mirt = mi/cond_true = mi/(hi + mi)
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
Consult Wikipedia for additional information.
mirt as the complement of
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.
mirt <- .15 # => sets a miss rate of 15% mirt <- 15/100 # => (decision = negative) for 15 out of 100 people with (condition = TRUE)