Specificity Calculator — True Negative Rate
Specificity is the proportion of actual negative cases that a test correctly identifies as negative. Enter true negatives (TN) and false positives (FP) to compute specificity, the false positive rate, and see the breakdown of correctly versus incorrectly classified negatives.
True negative rate — proportion of actual negatives correctly identified
- 1
Total actual negatives
90 + 10 = 100 - 2
Specificity (TNR)
90 ÷ 100 × 100 = 90Proportion of true negatives among all actual negative cases, expressed as a percentage.
How does this calculator work?
Specificity = TN / (TN + FP) — the fraction of truly negative cases correctly cleared by the test. Its complement, the false positive rate = FP / (TN + FP), is the fraction of healthy people falsely flagged. A perfect test has specificity = 100 % (zero false positives). Specificity is prevalence-independent; PPV is not.
Formula
How this is calculated
A diagnostic test applied to people who do not have the condition will sometimes return a positive result — a false alarm, or false positive (FP). The proportion of disease-free people it correctly flags as negative defines specificity: TN / (TN + FP). A test with 95 % specificity correctly clears 95 out of 100 healthy individuals; the remaining 5 % receive a false alarm (false positive rate = 5 %).
High specificity matters most when false positives carry serious consequences — for example, triggering an invasive follow-up procedure, causing significant anxiety, or leading to unnecessary treatment. A highly specific test is also said to be good at "ruling in" disease when it does return positive, because almost all its positives are real. This is the flip side of sensitivity (true positive rate), which measures how reliably the test detects actual cases; the two metrics trade off at any decision threshold.
Specificity is independent of disease prevalence in the tested population, unlike positive predictive value (PPV = TP/(TP+FP)), which rises when prevalence is high and falls when the condition is rare. For the complete set of diagnostic metrics — sensitivity, PPV, NPV, F1, likelihood ratios and Youden's J — use the Sensitivity and Specificity Calculator.
Frequently asked questions
Specificity depends only on performance among true negatives and is independent of disease prevalence in the population. PPV (positive predictive value = TP/(TP+FP)) answers "given a positive test, how likely is disease?" and changes with prevalence — the same test has a much lower PPV in a low-prevalence population, even with high specificity.
Prioritise high specificity when false positives carry serious downstream consequences: invasive confirmatory tests, unnecessary surgery, harmful treatments, or significant psychological impact. Screening tests often favour sensitivity to miss as few cases as possible, then use a highly specific confirmatory test to rule out false alarms.
It depends on prevalence and stakes. Screening a 1%-prevalence population with a 95%-specific test yields about 49.5 false positives per 1,000 screened versus ~9.5 true positives — giving a PPV of only ~16 %. In high-prevalence or routine clinical settings, 95 % specificity is excellent. The acceptable threshold depends on the cost and risk of follow-up procedures.
Also known as
TG we-Calculate Editorial Team. (2026). Specificity Calculator — True Negative Rate [Online calculator]. TG we-Calculate. https://we-calculate.com/calculator/specificity-calculator
TG we-Calculate Editorial Team. "Specificity Calculator — True Negative Rate." TG we-Calculate. 2026. https://we-calculate.com/calculator/specificity-calculator.
TG we-Calculate Editorial Team, "Specificity Calculator — True Negative Rate," TG we-Calculate, 2026. [Online]. Available: https://we-calculate.com/calculator/specificity-calculator
@misc{wecalculate_specificity_calculator, title = {Specificity Calculator — True Negative Rate}, author = {{TG we-Calculate Editorial Team}}, howpublished = {\url{https://we-calculate.com/calculator/specificity-calculator}}, year = {2026}, note = {TG we-Calculate} }
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