R/comp_prob_prob.R
comp_FDR.Rd
comp_FDR(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 false detection rate FDR
as a probability.
A warning is provided for NaN values.
comp_FDR
uses probabilities (not frequencies)
and does not round results.
comp_sens
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_FOR()
,
comp_NPV()
,
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_FDR(.50, .500, .500) # => FDR = 0.5 = (1 - PPV)
#> [1] 0.5
comp_FDR(.50, .333, .666) # => FDR = 0.5007 = (1 - PPV)
#> [1] 0.5007496