R/comp_prob_prob.R
comp_NPV.Rdcomp_NPV computes the negative predictive value NPV
from 3 essential probabilities
prev, sens, and spec.
comp_NPV(prev, sens, spec)The condition's prevalence prev
(i.e., the probability of condition being TRUE).
The decision's sensitivity sens
(i.e., the conditional probability of a positive decision
provided that the condition is TRUE).
The decision's specificity value spec
(i.e., the conditional probability
of a negative decision provided that the condition is FALSE).
The negative predictive value NPV as a probability.
A warning is provided for NaN values.
comp_NPV uses probabilities (not frequencies)
and does not round results.
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()
# (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