1. What is Sensitivity?

Sensitivity (also called the true positive rate) measures the proportion of actual positives that are correctly identified by a test. It's a crucial metric in statistics and diagnostic testing.

2. How Does the Calculator Work?

The calculator uses the sensitivity formula:

Where:

• \( TP \) — True positives (correctly identified positive cases)
• \( FN \) — False negatives (missed positive cases)

Explanation: Sensitivity ranges from 0 to 1, where 1 indicates perfect identification of all positive cases.

3. Importance of Sensitivity Calculation

Details: Sensitivity is critical in medical testing, quality control, and machine learning to evaluate how well a test identifies positive cases.

4. Using the Calculator

Tips: Enter the number of true positives and false negatives. Both values must be non-negative integers, and their sum must be greater than zero.

5. Frequently Asked Questions (FAQ)

Q1: What's the difference between sensitivity and specificity?
A: Sensitivity measures true positive rate, while specificity measures true negative rate.

Q2: What is a good sensitivity value?
A: Values closer to 1 are better. 0.9+ is excellent, 0.8-0.9 is good, below 0.7 may be problematic for critical tests.

Q3: When is high sensitivity most important?
A: When missing a positive case is dangerous (e.g., cancer screening, infectious disease detection).

Q4: Can sensitivity be calculated without false negatives?
A: No, both true positives and false negatives are needed to calculate sensitivity.

Q5: How does prevalence affect sensitivity?
A: Sensitivity itself isn't affected by prevalence, but predictive values are.