Positive predictive value and negative predictive value: Difference between revisions
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'''Positive predictive value''' (abbreviated '''PPV''') and '''negative predictive value''' (abbreviated '''NPV''') are statistical descriptors of diagnostic tests that depend on the prevalence. | '''Positive predictive value''' (abbreviated '''PPV''') and '''negative predictive value''' (abbreviated '''NPV''') are statistical descriptors of diagnostic tests that depend on the prevalence. | ||
==Positive predictive value== | |||
<br> | |||
:<math>PPV = \frac{TP}{TP+FP}</math> | |||
Where: | |||
*TP = true positives. | |||
*FP = false positives. | |||
==Negative predictive value== | |||
<br> | |||
:<math>NPV = \frac{TN}{TN+FN}</math> | |||
Where: | |||
*TN = true negatives. | |||
*FN = false negatives. | |||
==See also== | ==See also== | ||
Revision as of 14:10, 15 September 2017
Positive predictive value (abbreviated PPV) and negative predictive value (abbreviated NPV) are statistical descriptors of diagnostic tests that depend on the prevalence.
Positive predictive value
Where:
- TP = true positives.
- FP = false positives.
Negative predictive value
Where:
- TN = true negatives.
- FN = false negatives.