Sensitivity & Specificity Calculator
Enter the four cells of a 2x2 contingency table (true positives, false positives, false negatives, true negatives) to compute all major diagnostic test performance metrics.
What is Sensitivity?
Sensitivity (also called recall or true positive rate) measures how well a test detects the condition when it is actually present:
Sensitivity = TP / (TP + FN)
A highly sensitive test rarely misses true cases, making it useful for screening.
What is Specificity?
Specificity (true negative rate) measures how well a test correctly identifies those without the condition:
Specificity = TN / (TN + FP)
A highly specific test rarely produces false alarms, making it useful for confirmation.
Predictive Values
- PPV (Positive Predictive Value) = TP / (TP + FP) -- given a positive result, the probability the condition is truly present
- NPV (Negative Predictive Value) = TN / (TN + FN) -- given a negative result, the probability the condition is truly absent
PPV and NPV depend on prevalence: the same test performs differently in high-prevalence vs. low-prevalence populations.
Likelihood Ratios
- LR+ = Sensitivity / (1 - Specificity): how much a positive test increases the odds
- LR- = (1 - Sensitivity) / Specificity: how much a negative test decreases the odds
An LR+ above 10 or LR- below 0.1 represents a strong diagnostic test.