ppod
defines the proportion (baseline probability or rate) of
a decision being positive
(but not necessarily accurate/correct).
ppod
An object of class numeric
of length 1.
ppod
is also known as bias
, though the latter term is also
used to describe a systematic tendency to deviate in any --- rather
than just positive --- direction.
Understanding or obtaining the proportion of positive decisions ppod
:
Definition:
ppod
is the (non-conditional) probability:
ppod = p(decision = positive)
or the base rate (or baseline probability) of a decision being positive (but not necessarily accurate/correct).
Perspective:
ppod
classifies a population of N
individuals
by decision (ppod = dec_pos/N
).
ppod
is the "by decision" counterpart to prev
(which adopts a "by condition" perspective).
Alternative names:
base rate of positive decisions (PR
),
proportion predicted or diagnosed,
rate of decision = positive
cases
In terms of frequencies,
ppod
is the ratio of
dec_pos
(i.e., hi + fa
)
divided by N
(i.e.,
hi + mi
+ fa + cr
):
ppod = dec_pos/N = (hi + fa)/(hi + mi + fa + cr)
Dependencies:
ppod
is a feature of the decision process
or diagnostic procedure.
However, the conditional probabilities
sens
, mirt
,
spec
, fart
,
PPV
, and NPV
also depend on the condition's prevalence prev
.
Consult Wikipedia for additional information.
prob
contains current probability information;
comp_prob
computes current probability information;
num
contains basic numeric parameters;
init_num
initializes basic numeric parameters;
freq
contains current frequency information;
comp_freq
computes current frequency information;
is_prob
verifies probabilities.
Other probabilities:
FDR
,
FOR
,
NPV
,
PPV
,
acc
,
err
,
fart
,
mirt
,
prev
,
sens
,
spec
ppod <- .50 # sets a rate of positive decisions of 50%
ppod <- 50/100 # (decision = TRUE) for 50 out of 100 individuals
is_prob(ppod) # TRUE
#> [1] TRUE