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

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_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_prob, comp_sens, comp_spec

Examples

# (1) Ways to work: comp_NPV(.50, .500, .500) # => NPV = 0.5
#> [1] 0.5
comp_NPV(.50, .333, .666) # => NPV = 0.4996
#> [1] 0.4996249
# (2) Watch out for vectors: prev <- seq(0, 1, .1) comp_NPV(prev, .5, .5) # => without NaN values
#> [1] 1.0 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0.0
comp_NPV(prev, 1, 0) # => with NaN values
#> Warning: NPV is NaN.
#> [1] NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN
# (3) Watch out for extreme values: comp_NPV(1, 1, 1) # => NaN, as cr = 0 and mi = 0: 0/0
#> Warning: NPV is NaN.
#> [1] NaN
comp_NPV(1, 1, 0) # => NaN, as cr = 0 and mi = 0: 0/0
#> Warning: NPV is NaN.
#> [1] NaN
comp_NPV(.5, sens = 1, spec = 0) # => NaN, no dec_neg cases: NPV = 0/0 = NaN
#> Warning: NPV is NaN.
#> [1] NaN
is_extreme_prob_set(.5, sens = 1, spec = 0) # => verifies extreme cases
#> Warning: Extreme case (sens = 1 & spec = 0): #> 0 mi (FN) and 0 cr (TN) cases; 0 dec_neg cases; NPV = NaN.
#> [1] TRUE