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_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 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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