sens defines a decision's sensitivity (or hit rate) value:
The conditional probability of the decision being positive
if the condition is
An object of class
numeric of length 1.
Understanding or obtaining the sensitivity
(or hit rate
sens is the conditional probability
for a (correct) positive decision given that
the condition is
sens = p(decision = positive | condition = TRUE)
or the probability of correctly detecting true cases
condition = TRUE).
sens further classifies
the subset of
by decision (
sens = hi/cond_true).
true positive rate (
hit rate (
probability of detection,
power = 1 - beta,
sens is the complement of the miss rate
mirt (aka. false negative rate
FNR or the
rate of Type-II errors):
sens = (1 - miss rate) = (1 - FNR)
sens is the opposite conditional probability
-- but not the complement --
of the positive predictive value
PPV = p(condition = TRUE | decision = positive)
sens = hi/cond_true = hi/(hi + mi)
sens is a feature of a decision process
or diagnostic procedure and a measure of
correct decisions (true positives).
Due to being a conditional probability,
the value of
sens is not intrinsic to
the decision process, but also depends on the
condition's prevalence value
Consult Wikipedia for additional information.
sens 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.
sens <- .85 # sets a sensitivity value of 85% sens <- 85/100 # (decision = positive) for 85 out of 100 people with (condition = TRUE) is_prob(sens) # TRUE#>  TRUE