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Edited by: Published: 2018
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Specificity refers to a test’s accuracy at identifying those who do not have a condition or characteristic. It is the proportion of truly not at-risk or without condition (e.g., trait, disease, classification, and label) who are correctly identified as such through a diagnostic tool. Specificity describes the characteristic of a test in terms of how well the test correctly identifies true negatives (TNs) or those who do not have the predicted condition. Mathematically, it is expressed as the proportion of TN results to the sum of both true-negative and false-positive results. Mathematically, this can be expressed as:

px=number of true negatives/       (number of true negatives+false positives).

To better understand specificity, imagine describing a test along two dimensions depicting the relation between the predicted conditions. These dimensions can be further divided along four quadrants (see Figure ...

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