StATS: What is a negative predictive value?

The negative predictive value of a test is the probability that the patient will not have the disease when restricted to all patients who test negative.

You can compute the negative predictive value as

NPV = TN / (TN + FN)

where TN and FN are the number of true negative and false negative results, respectively. Notice that the denominator for negative predictive value is the number of patients who test negative. You can also define the negative predictive value using conditional probabilities,

NPV = P [ Patient is healthy | Test is negative ].

If the prevalence of the disease in your situation is different from the prevalence of the disease in the research study you are examining, then you can use likelihood ratios to estimate the NPV.

The following table summarizes these calculations.

Do not calculate the negative predictive value on a sample where the prevalence of the disease was artificially controlled. For example, the NPV is meaningless in a study where you artificially recruited healthy and diseased patients in a one to one ratio.

Here is an example.

This page was written by Steve Simon while working at Children's Mercy Hospital. Although I do not hold the copyright for this material, I am reproducing it here as a service, as it is no longer available on the Children's Mercy Hospital website. Need more information? I have a page with general help resources. You can also browse for pages similar to this one at Category: Definitions, Category: Diagnostic testing.