comp_ppod computes the proportion of positive decisions ppod from 3 essential probabilities prev, sens, and spec.

comp_ppod(prev, sens, spec)

## Arguments

prev 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).

## 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_accu_freq, comp_accu_prob, comp_acc, comp_comp_pair, comp_complement, comp_complete_prob_set, comp_err, comp_fart, comp_mirt, comp_prob_freq, comp_prob, comp_sens, comp_spec

## Examples

# (1) ways to work:
comp_ppod(.10, .200, .300)  # => ppod = 0.65#>  0.65comp_ppod(.50, .333, .666)  # => ppod = 0.3335#>  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#>   0.50 0.53 0.56 0.59 0.62 0.65 0.68 0.71 0.74 0.77 0.80comp_ppod(prev,  0,  1)  # => 0 0 0 0 0 0 0 0 0 0 0#>   0 0 0 0 0 0 0 0 0 0 0
# (3) watch out for extreme values:
comp_ppod(1, 1, 1)  #  => 1#>  1comp_ppod(1, 1, 0)  #  => 1#>  1
comp_ppod(1, 0, 1)  #  => 0#>  0comp_ppod(1, 0, 0)  #  => 0#>  0
comp_ppod(0, 1, 1)  #  => 0#>  0comp_ppod(0, 1, 0)  #  => 1#>  1
comp_ppod(0, 0, 1)  #  => 0#>  0comp_ppod(0, 0, 0)  #  => 1#>  1