R/init_prob.R
sens.Rd
sens
defines a decision's sensitivity (or hit rate) value:
The conditional probability of the decision being positive
if the condition is TRUE
.
sens
An object of class numeric
of length 1.
Understanding or obtaining the sensitivity sens
(or hit rate HR
):
Definition: sens
is the conditional probability
for a (correct) positive decision given that
the condition is TRUE
:
sens = p(decision = positive | condition = TRUE)
or the probability of correctly detecting true cases
(condition = TRUE
).
Perspective:
sens
further classifies
the subset of cond_true
individuals
by decision (sens = hi/cond_true
).
Alternative names:
true positive rate (TPR
),
hit rate (HR
),
probability of detection,
power = 1 - beta
,
recall
Relationships:
a. 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)
b. sens
is the opposite conditional probability
-- but not the complement --
of the positive predictive value PPV
:
PPV = p(condition = TRUE | decision = positive)
In terms of frequencies,
sens
is the ratio of
hi
divided by
cond_true
(i.e., hi + mi
):
sens = hi/cond_true = hi/(hi + mi)
Dependencies:
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 prev
.
Consult Wikipedia for additional information.
comp_sens
computes sens
as the complement of mirt
;
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
,
mirt
,
ppod
,
prev
,
spec
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
#> [1] TRUE