is_extreme_prob_set {riskyr} | R Documentation |
Verify that a set of probabilities describes an extreme case.
Description
is_extreme_prob_set
verifies that a set
of probabilities (i.e., prev
,
and sens
or mirt
,
and spec
or fart
)
describe an extreme case.
Usage
is_extreme_prob_set(prev, sens = NA, mirt = NA, spec = NA, fart = NA)
Arguments
prev |
The condition's prevalence value |
sens |
The decision's sensitivity |
mirt |
The decision's miss rate |
spec |
The decision's specificity |
fart |
The decision's false alarm rate |
Details
If TRUE
, a warning message describing the
nature of the extreme case is printed to allow
anticipating peculiar effects (e.g., that
PPV
or NPV
values
cannot be computed or are NaN
).
This function does not verify the type, range, sufficiency,
or consistency of its arguments. See is_prob
,
is_suff_prob_set
, is_complement
,
is_valid_prob_pair
and
is_valid_prob_set
for these purposes.
Value
A Boolean value:
TRUE
if an extreme case is identified;
otherwise FALSE
.
See Also
is_valid_prob_pair
verifies that a pair of probabilities can be complements;
is_valid_prob_set
verifies the validity of a set of probability inputs;
num
contains basic numeric variables;
init_num
initializes basic numeric variables;
prob
contains current probability information;
comp_prob
computes current probability information;
freq
contains current frequency information;
comp_freq
computes current frequency information;
as_pc
displays a probability as a percentage;
as_pb
displays a percentage as probability
Other verification functions:
is_complement()
,
is_freq()
,
is_integer()
,
is_matrix()
,
is_perc()
,
is_prob()
,
is_suff_prob_set()
,
is_valid_prob_pair()
,
is_valid_prob_set()
,
is_valid_prob_triple()
Examples
# Identify 6 extreme cases (+ 4 variants):
is_extreme_prob_set(1, 1, NA, 1, NA) # => TRUE + warning: N true positives
plot_tree(1, 1, NA, 1, NA, N = 100) # => illustrates this case
is_extreme_prob_set(1, 0, NA, 1, NA) # => TRUE + warning: N false negatives
plot_tree(1, 0, NA, 1, NA, N = 200) # => illustrates this case
sens <- .50
is_extreme_prob_set(0, sens, NA, 0, NA) # => TRUE + warning: N false positives
plot_tree(0, sens, NA, 0, N = 300) # => illustrates this case
# Variant:
is_extreme_prob_set(0, sens, NA, NA, 1) # => TRUE + warning: N false positives
plot_tree(0, sens, NA, NA, 1, N = 350) # => illustrates this case
sens <- .50
is_extreme_prob_set(0, sens, NA, 1) # => TRUE + warning: N true negatives
plot_tree(0, sens, NA, NA, 1, N = 400) # => illustrates this case
# Variant:
is_extreme_prob_set(0, sens, NA, NA, 0) # => TRUE + warning: N true negatives
plot_tree(0, sens, NA, NA, 0, N = 450) # => illustrates this case
prev <- .50
is_extreme_prob_set(prev, 0, NA, 1, NA) # => TRUE + warning: 0 hi and 0 fa (0 dec_pos cases)
plot_tree(prev, 0, NA, 1, NA, N = 500) # => illustrates this case
# # Variant:
is_extreme_prob_set(prev, 0, 0, NA, 0) # => TRUE + warning: 0 hi and 0 fa (0 dec_pos cases)
plot_tree(prev, 0, NA, 1, NA, N = 550) # => illustrates this case
prev <- .50
is_extreme_prob_set(prev, 1, NA, 0, NA) # => TRUE + warning: 0 mi and 0 cr (0 dec_neg cases)
plot_tree(prev, 1, NA, 0, NA, N = 600) # => illustrates this case
# # Variant:
is_extreme_prob_set(prev, 1, NA, 0, NA) # => TRUE + warning: 0 mi and 0 cr (0 dec_neg cases)
plot_tree(prev, 1, NA, 0, NA, N = 650) # => illustrates this case