NPV defines some decision's negative predictive value (NPV): The conditional probability of the condition being FALSE provided that the decision is negative.

NPV

## Format

An object of class numeric of length 1.

## Details

Understanding or obtaining the negative predictive value NPV:

• Definition: NPV is the conditional probability for the condition being FALSE given a negative decision:

NPV = p(condition = FALSE | decision = negative)

or the probability of a negative decision being correct.

• Perspective: NPV further classifies the subset of dec_neg individuals by condition (NPV = cr/dec_neg = cr/(mi + cr)).

• Alternative names: true omission rate

• Relationships:

a. NPV is the complement of the false omission rate FOR:

NPV = 1 - FOR

b. NPV is the opposite conditional probability -- but not the complement -- of the specificity spec:

spec = p(decision = negative | condition = FALSE)

• In terms of frequencies, NPV is the ratio of cr divided by dec_neg (i.e., cr + mi):

NPV = cr/dec_neg = cr/(cr + mi)

• Dependencies: NPV is a feature of a decision process or diagnostic procedure and -- similar to the specificity spec -- a measure of correct decisions (negative decisions that are actually FALSE).

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

## References

comp_NPV computes NPV; 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, PPV, acc, err, fart, mirt, ppod, prev, sens, spec
NPV <- .95     # sets a negative predictive value of 95%