Positive and negative predictive values
Positive and Negative Predictive Values
Positive predictive value (PPV) and negative predictive value (NPV) are statistical measures commonly used in diagnostic testing and biostatistics.
Pronunciation
- Positive predictive value: /ˈpɒzɪtɪv prɪˈdɪktɪv ˈvæljuː/
- Negative predictive value: /ˈnɛɡətɪv prɪˈdɪktɪv ˈvæljuː/
Etymology
The terms "positive predictive value" and "negative predictive value" were first used in the field of epidemiology in the late 20th century. The words "positive" and "negative" refer to the presence or absence of a condition, while "predictive value" refers to the predictive power of a test.
Definition
The positive predictive value (PPV) is the probability that subjects with a positive screening test truly have the disease. The negative predictive value (NPV) is the probability that subjects with a negative screening test truly don't have the disease.
Calculation
The PPV and NPV are calculated using the formulas:
- PPV = True positives / (True positives + False positives)
- NPV = True negatives / (True negatives + False negatives)
Related Terms
- Sensitivity (tests): The ability of a test to correctly identify those with the disease.
- Specificity (tests): The ability of a test to correctly identify those without the disease.
- Prevalence: The proportion of a population who have a specific characteristic in a given time period.
- Likelihood ratios in diagnostic testing: The likelihood that a given test result would be expected in a patient with the target disorder compared to the likelihood that that same result would be expected in a patient without the target disorder.
External links
- Medical encyclopedia article on Positive and negative predictive values
- Wikipedia's article - Positive and negative predictive values
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