riskyr (version 0.2.0)

is_extreme_prob_set: 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 prev (i.e., the probability of condition being TRUE).

sens

The decision's sensitivity sens (i.e., the conditional probability of a positive decision provided that the condition is TRUE). sens is optional when is complement mirt is provided.

mirt

The decision's miss rate mirt (i.e., the conditional probability of a negative decision provided that the condition is TRUE). mirt is optional when is complement sens is provided.

spec

The decision's specificity spec (i.e., the conditional probability of a negative decision provided that the condition is FALSE). spec is optional when is complement fart is provided.

fart

The decision's false alarm rate fart (i.e., the conditional probability of a positive decision provided that the condition is FALSE). fart is optional when its complement spec is provided.

Value

A Boolean value: TRUE if an extreme case is identified; otherwise FALSE.

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.

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_perc, is_prob, is_suff_prob_set, is_valid_prob_pair, is_valid_prob_set, is_valid_prob_triple

Examples

Run this code
# NOT RUN {
# 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

# }

Run the code above in your browser using DataCamp Workspace