View source: R/comp_prob_prob.R
comp_PPV | R Documentation |
comp_PPV
computes the positive predictive value PPV
from 3 essential probabilities
prev
, sens
, and spec
.
comp_PPV(prev, sens, spec)
prev |
The condition's prevalence |
sens |
The decision's sensitivity |
spec |
The decision's specificity value |
comp_PPV
uses probabilities (not frequencies)
and does not round results.
The positive predictive value PPV
as a probability.
A warning is provided for NaN values.
comp_sens
and comp_NPV
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_NPV()
,
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_PPV(.50, .500, .500) # => PPV = 0.5 comp_PPV(.50, .333, .666) # => PPV = 0.499 # (2) Watch out for vectors: prev <- seq(0, 1, .1) comp_PPV(prev, .5, .5) # => without NaN values comp_PPV(prev, 0, 1) # => with NaN values # (3) Watch out for extreme values: comp_PPV(prev = 1, sens = 0, spec = .5) # => NaN, only mi: hi = 0 and fa = 0: PPV = 0/0 = NaN is_extreme_prob_set(prev = 1, sens = 0, spec = .5) # => verifies extreme cases comp_PPV(prev = 0, sens = .5, spec = 1) # => NaN, only cr: hi = 0 and fa = 0: PPV = 0/0 = NaN is_extreme_prob_set(prev = 0, sens = .5, spec = 1) # => verifies extreme cases comp_PPV(prev = .5, sens = 0, spec = 1) # => NaN, only cr: hi = 0 and fa = 0: PPV = 0/0 = NaN is_extreme_prob_set(prev = .5, sens = 0, spec = 1) # => verifies extreme cases
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