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How are the predictive values of a test different from the sensitivity and specificity of a test?

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Final answer:

Predictive values are used to determine the probability of a positive or negative test result, while sensitivity and specificity measure the accuracy of a test.

Step-by-step explanation:

The predictive values of a test are different from the sensitivity and specificity of a test. Predictive values are used to determine the probability that a positive or negative test result is correct. There are two types of predictive values: positive predictive value (PPV) and negative predictive value (NPV).

Sensitivity and specificity, on the other hand, are measures of the accuracy of a test. Sensitivity is the ability of a test to correctly identify individuals who have the condition (true positives), while specificity is the ability of a test to correctly identify individuals who do not have the condition (true negatives).

For example, let's consider a COVID-19 test. If the test has a sensitivity of 90%, it means that 90% of the individuals who are infected with COVID-19 will test positive (true positives). If the test has a specificity of 95%, it means that 95% of the individuals who are not infected with COVID-19 will test negative (true negatives).

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