Compute the proportion of positive decisions (ppod) from probabilities.
Source:R/comp_prob_prob.R
comp_ppod.Rdcomp_ppod computes the proportion of positive decisions ppod
from 3 essential probabilities
prev, sens, and spec.
Arguments
- prev
The condition's prevalence
prev(i.e., the probability of condition beingTRUE).- sens
The decision's sensitivity
sens(i.e., the conditional probability of a positive decision provided that the condition isTRUE).- spec
The decision's specificity value
spec(i.e., the conditional probability of a negative decision provided that the condition isFALSE).
Value
The proportion of positive decisions ppod as a probability.
A warning is provided for NaN values.
Details
comp_ppod uses probabilities (not frequencies) as
inputs and returns a proportion (probability)
without rounding.
Definition: ppod is
proportion (or probability) of positive decisions:
ppod = dec_pos/N = (hi + fa)/(hi + mi + fa + cr)
Values range from 0 (only negative decisions) to 1 (only positive decisions).
Importantly, positive decisions dec_pos
are not necessarily correct decisions dec_cor.
See also
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_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_prob(),
comp_prob_freq(),
comp_sens(),
comp_spec()
Examples
# (1) ways to work:
comp_ppod(.10, .200, .300) # => ppod = 0.65
#> [1] 0.65
comp_ppod(.50, .333, .666) # => ppod = 0.3335
#> [1] 0.3335
# (2) watch out for vectors:
prev <- seq(0, 1, .1)
comp_ppod(prev, .8, .5) # => 0.50 0.53 0.56 0.59 0.62 0.65 0.68 0.71 0.74 0.77 0.80
#> [1] 0.50 0.53 0.56 0.59 0.62 0.65 0.68 0.71 0.74 0.77 0.80
comp_ppod(prev, 0, 1) # => 0 0 0 0 0 0 0 0 0 0 0
#> [1] 0 0 0 0 0 0 0 0 0 0 0
# (3) watch out for extreme values:
comp_ppod(1, 1, 1) # => 1
#> [1] 1
comp_ppod(1, 1, 0) # => 1
#> [1] 1
comp_ppod(1, 0, 1) # => 0
#> [1] 0
comp_ppod(1, 0, 0) # => 0
#> [1] 0
comp_ppod(0, 1, 1) # => 0
#> [1] 0
comp_ppod(0, 1, 0) # => 1
#> [1] 1
comp_ppod(0, 0, 1) # => 0
#> [1] 0
comp_ppod(0, 0, 0) # => 1
#> [1] 1