Question

Describe the following for a given test: 
Negative predictive value. 
 

Hint:

Negative predictive value increases with lower disease prevalence and a higher specificity of the test.

Answer 1

Step 1: Defining Negative Predictive Value (NPV).
Negative Predictive Value refers to the probability that subjects with a negative test result truly do not have the disease. It indicates the likelihood that a negative test result is a true negative.

Step 2: Formula for Negative Predictive Value.
\[ \text{NPV} = \frac{\text{True Negatives}}{\text{True Negatives + False Negatives}} \] Where:
- True Negatives (TN): The number of people who do not have the disease and test negative.
- False Negatives (FN): The number of people who have the disease but test negative.

Step 3: Conclusion.
A high NPV means that a negative test result is highly likely to be accurate, and the person truly does not have the disease. This is important for ruling out a disease when a person tests negative.