riskyr (version 0.1.0)

comp_NPV: Compute a decision's negative predictive value (NPV) from probabilities.

Description

comp_NPV computes the negative predictive value NPV from 3 essential probabilities prev, sens, and spec.

Usage

comp_NPV(prev, sens, spec)

Arguments

prev

The condition's prevalence 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).

spec

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

Value

The negative predictive value NPV as a probability. A warning is provided for NaN values.

Details

comp_NPV uses probabilities (not frequencies) and does not round results.

See Also

comp_spec and comp_PPV compute related probabilities; is_extreme_prob_set verifies extreme cases; comp_complement computes a probability's complement; is_complement verifies probability complements; comp_prob computes current probability information; prob contains current probability information; is_prob verifies probabilities.

Other functions computing probabilities: comp_FDR, comp_FOR, comp_PPV, comp_accu, comp_acc, comp_comp_pair, comp_complement, comp_complete_prob_set, comp_fart, comp_mirt, comp_ppod, comp_prob_freq, comp_prob, comp_sens, comp_spec

Examples

# NOT RUN {
# (1) Ways to work:
comp_NPV(.50, .500, .500)  # => NPV = 0.5
comp_NPV(.50, .333, .666)  # => NPV = 0.4996

# (2) Watch out for vectors:
prev <- seq(0, 1, .1)
comp_NPV(prev, .5, .5)  # => without NaN values
comp_NPV(prev,  1,  0)  # => with NaN values

# (3) Watch out for extreme values:
comp_NPV(1, 1, 1)   # => NaN, as cr = 0 and mi = 0: 0/0
comp_NPV(1, 1, 0)   # => NaN, as cr = 0 and mi = 0: 0/0
comp_NPV(.5, sens = 1, spec = 0)  # => NaN, no dec.neg cases:  NPV = 0/0 = NaN
is_extreme_prob_set(.5, sens = 1, spec = 0)  # => verifies extreme cases


# }