1. What are Sensitivity and Specificity?

Sensitivity (true positive rate) measures the proportion of actual positives correctly identified. Specificity (true negative rate) measures the proportion of actual negatives correctly identified. These metrics are fundamental in evaluating diagnostic tests.

2. How Does the Calculator Work?

The calculator uses these equations:

Where:

• \( TP \) — True Positives (correctly identified cases)
• \( FN \) — False Negatives (missed cases)
• \( TN \) — True Negatives (correctly rejected cases)
• \( FP \) — False Positives (incorrectly identified cases)

3. Clinical Importance

Details: Sensitivity is crucial when missing a case has severe consequences. Specificity is important when false positives lead to unnecessary treatments or anxiety. The ideal test has both high sensitivity and specificity.

4. Using the Calculator

Tips: Enter the counts from your 2×2 contingency table. All values must be non-negative integers. Results are presented as percentages.

5. Frequently Asked Questions (FAQ)

Q1: What's considered good sensitivity/specificity?
A: Generally >90% is excellent, 80-90% is good, and <70% may be problematic depending on context.

Q2: Can a test have 100% sensitivity and specificity?
A: Rarely in practice. Perfect metrics usually indicate overfitting or problems with the test population.

Q3: How are these different from PPV and NPV?
A: PPV/NPV depend on prevalence, while sensitivity/specificity are intrinsic test characteristics.

Q4: What if my FN or FP is zero?
A: The calculator handles these cases, but perfect scores may warrant verification with larger samples.

Q5: How do prevalence affect these metrics?
A: Prevalence doesn't affect sensitivity/specificity but does affect predictive values.