comp_prob: Compute probabilities from (3 essential) probabilities.

Description Usage Arguments Details Value See Also Examples

View source: R/init_prob_num.R

Description

comp_prob computes current probability information from 3 essential probabilities (prev, sens or mirt, spec or fart). It returns a list of 13 probabilities prob as its output.

Usage

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comp_prob(prev = num$prev, sens = num$sens, mirt = NA,
  spec = num$spec, fart = NA, tol = 0.01)

Arguments

prev

The condition's prevalence value prev (i.e., the probability of the condition being TRUE).

sens

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

mirt

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

spec

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

tol

A numeric tolerance value for is_complement. Default: tol = .01.

Details

comp_prob assumes that a sufficient and consistent set of essential probabilities (i.e., prev and either sens or its complement mirt, and either spec or its complement fart) is provided.

comp_prob computes and returns a full set of basic and various derived probabilities (e.g., the probability of a positive decision ppod, the probability of a correct decision acc, the predictive values PPV and NPV, as well as their complements FDR and FOR) in its output of a list prob.

Extreme probabilities (sets containing two or more probabilities of 0 or 1) may yield unexpected values (e.g., predictive values PPV or NPV turning NaN when is_extreme_prob_set evaluates to TRUE).

comp_prob is the probability counterpart to the frequency function comp_freq.

Key relationships between probabilities and frequencies:

Functions translating between representational formats: comp_prob_prob, comp_prob_freq, comp_freq_prob, comp_freq_freq (see documentation of comp_prob_prob for details).

Value

A list prob containing 13 probability values.

See Also

prob contains current probability information; accu contains current accuracy information; num contains basic numeric parameters; init_num initializes basic numeric parameters; pal contains current color information; txt contains current text information; freq contains current frequency information; comp_freq computes frequencies from probabilities; is_valid_prob_set verifies sets of probability inputs; is_extreme_prob_set verifies sets of extreme probabilities; comp_min_N computes a suitable minimum population size N; comp_freq_freq computes current frequency information from (4 essential) frequencies; comp_freq_prob computes current frequency information from (3 essential) probabilities; comp_prob_freq computes current probability information from (4 essential) frequencies; comp_prob_prob computes current probability information from (3 essential) probabilities.

Other functions computing probabilities: comp_FDR, comp_FOR, comp_NPV, comp_PPV, comp_accu_freq, comp_accu_prob, comp_acc, comp_comp_pair, comp_complement, comp_complete_prob_set, comp_err, comp_fart, comp_mirt, comp_ppod, comp_prob_freq, comp_sens, comp_spec

Examples

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# Basics:
comp_prob(prev = .11, sens = .88, spec = .77)                        # => ok: PPV = 0.3210614
comp_prob(prev = .11, sens = NA, mirt = .12, spec = NA, fart = .23)  # => ok: PPV = 0.3210614
comp_prob()          # => ok, using current defaults
length(comp_prob())  # => 13 probabilities

# Ways to work:
comp_prob(.99, sens = .99, spec = .99)              # => ok: PPV = 0.999898
comp_prob(.99, sens = .90, spec = NA, fart = .10)   # => ok: PPV = 0.9988789

# Watch out for extreme cases:
comp_prob(1, sens = 0, spec = 1)      # => ok, but with warnings (as PPV & FDR are NaN)
comp_prob(1, sens = 0, spec = 0)      # => ok, but with warnings (as PPV & FDR are NaN)
comp_prob(1, sens = 0, spec = NA, fart = 0)  # => ok, but with warnings (as PPV & FDR are NaN)
comp_prob(1, sens = 0, spec = NA, fart = 1)  # => ok, but with warnings (as PPV & FDR are NaN)

# Watch out for extreme cases:
comp_prob(1, sens = 0, spec = 1)      # => ok, but with warnings (as PPV & FDR are NaN)
comp_prob(1, sens = 0, spec = 0)      # => ok, but with warnings (as PPV & FDR are NaN)
comp_prob(1, sens = 0, spec = NA, fart = 0)  # => ok, but with warnings (as PPV & FDR are NaN)
comp_prob(1, sens = 0, spec = NA, fart = 1)  # => ok, but with warnings (as PPV & FDR are NaN)

comp_prob(1, sens = 1, spec = 0)      # => ok, but with warnings (as NPV & FOR are NaN)
comp_prob(1, sens = 1, spec = 1)      # => ok, but with warnings (as NPV & FOR are NaN)
comp_prob(1, sens = 1, spec = NA, fart = 0)  # => ok, but with warnings (as NPV & FOR are NaN)
comp_prob(1, sens = 1, spec = NA, fart = 1)  # => ok, but with warnings (as NPV & FOR are NaN)

# Ways to fail:
comp_prob(NA, 1, 1, NA)  # => only warning: invalid set (prev not numeric)
comp_prob(8,  1, 1, NA)  # => only warning: prev no probability
comp_prob(1,  8, 1, NA)  # => only warning: sens no probability
comp_prob(1,  1, 1,  1)  # => only warning: is_complement not in tolerated range

riskyr documentation built on Jan. 3, 2019, 1:06 a.m.