How does one determine if a test is accuracy? What does accuracy mean? One measure of test precision it is the positive predictive value, or the share of positive test results which are actually positive. Alternatively, the negative predictive value determines the share of negative test results which are true (rather than false) negatives. Better positive and negative predictive value indicates a better test.
In addition, sensitivity and specificity uses the gold standard (i.e., “true”) results as the denominator. Sensitivity indicates the share of true positives as a fraction of total people who actually have the condition. Similarly, specificity gives the number of true negatives as a share of the number of test subjects who actually had the disease.
The formulas for these four metrics describing the accuracy of various diagnostic testing procedures is shown below:
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Positive Predictive Value: TP/(TP+FP)
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Negative Predictive Value: TN/(TN+FN)
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Sensitivity: TP/(TP+FN)
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Specificity: TN/(FP+TN)
This example below from Wikipedia provides a simple example.