View source: R/comp_prob_prob.R
| comp_NPV | R Documentation |
comp_NPV computes the negative predictive value NPV
from 3 essential probabilities
prev, sens, and spec.
comp_NPV(prev, sens, spec)
prev |
The condition's prevalence |
sens |
The decision's sensitivity |
spec |
The decision's specificity value |
comp_NPV uses probabilities (not frequencies)
and does not round results.
The negative predictive value NPV as a probability.
A warning is provided for NaN values.
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_acc(),
comp_accu_freq(),
comp_accu_prob(),
comp_comp_pair(),
comp_complement(),
comp_complete_prob_set(),
comp_err(),
comp_fart(),
comp_mirt(),
comp_ppod(),
comp_prob(),
comp_prob_freq(),
comp_sens(),
comp_spec()
# (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
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