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 are fundamental metrics for evaluating diagnostic tests.

2. How Does the Calculator Work?

The calculator uses these formulas:

Where:

• True Positives (TP) — Correctly identified positive cases
• Total Positives — All actual positive cases (TP + FN)
• True Negatives (TN) — Correctly identified negative cases
• Total Negatives — All actual negative cases (TN + FP)

3. Clinical Importance

Details: Sensitivity is crucial when missing a positive case is dangerous. Specificity is important when falsely labeling someone as positive has serious consequences. Ideal tests have both high sensitivity and specificity.

4. Using the Calculator

Tips: Enter the true positives, total positives, true negatives, and total negatives from your test results. All values must be non-negative integers.

5. Frequently Asked Questions (FAQ)

Q1: What's a good sensitivity value?
A: Generally >90% is excellent, 80-90% is good, below 80% may be problematic for screening tests.

Q2: What's a good specificity value?
A: >95% is excellent, 90-95% is good, below 90% may lead to too many false positives.

Q3: Can a test have 100% sensitivity and specificity?
A: In theory yes, but in practice perfect tests are extremely rare due to biological variability.

Q4: What's the relationship with PPV and NPV?
A: Positive/Negative Predictive Values also depend on disease prevalence, while sensitivity/specificity don't.

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