PPV defines some decision's positive predictive value (PPV): The conditional probability of the condition being TRUE provided that the decision is positive.

PPV

## Format

An object of class numeric of length 1.

## Details

Understanding or obtaining the positive predictive value PPV:

• Definition: PPV is the conditional probability for the condition being TRUE given a positive decision:

PPV = p(condition = TRUE | decision = positive)

or the probability of a positive decision being correct.

• Perspective: PPV further classifies the subset of dec_pos individuals by condition (PPV = hi/dec_pos = hi/(hi + fa)).

• Alternative names: precision

• Relationships:

a. PPV is the complement of the false discovery or false detection rate FDR:

PPV = 1 - FDR

b. PPV is the opposite conditional probability -- but not the complement -- of the sensitivity sens:

sens = p(decision = positive | condition = TRUE)

• In terms of frequencies, PPV is the ratio of hi divided by dec_pos (i.e., hi + fa):

PPV = hi/dec_pos = hi/(hi + fa)

• Dependencies: PPV is a feature of a decision process or diagnostic procedure and -- similar to the sensitivity sens -- a measure of correct decisions (positive decisions that are actually TRUE).

However, due to being a conditional probability, the value of PPV is not intrinsic to the decision process, but also depends on the condition's prevalence value prev.

## References

comp_PPV computes PPV; prob contains current probability information; comp_prob computes current probability information; num contains basic numeric parameters; init_num initializes basic numeric parameters; comp_freq computes current frequency information; is_prob verifies probabilities.
Other probabilities: FDR, FOR, NPV, acc, err, fart, mirt, ppod, prev, sens, spec
PPV <- .55     # sets a positive predictive value of 55%