1. What is Sample Size Calculation for Sensitivity?

The sample size calculation for sensitivity determines how many participants are needed in a diagnostic study to estimate sensitivity with a desired precision. Sensitivity is the ability of a test to correctly identify those with the disease (true positive rate).

2. How Does the Calculator Work?

The calculator uses the following formula:

Where:

• \( Z \) — Z-score for desired confidence level (1.96 for 95% CI)
• \( Sens \) — Expected sensitivity (as decimal, e.g., 0.9 for 90%)
• \( d \) — Desired precision (margin of error, as decimal)

Explanation: The formula calculates the minimum number of participants needed to estimate sensitivity within a specified confidence interval.

3. Importance of Sample Size Calculation

Details: Proper sample size ensures your study has adequate power to detect clinically meaningful differences and provides precise estimates of diagnostic accuracy.

4. Using the Calculator

Tips:

• For 95% confidence, use Z=1.96
• Enter sensitivity as decimal (0-1)
• Precision (d) is typically 0.05-0.10
• All values must be positive numbers

5. Frequently Asked Questions (FAQ)

Q1: What Z-score should I use?
A: For 95% confidence interval, use 1.96. For 90% CI use 1.645, and for 99% CI use 2.576.

Q2: How do I estimate expected sensitivity?
A: Use values from previous studies or pilot data. If unknown, use 0.5 for most conservative estimate.

Q3: What's a reasonable precision value?
A: Typically ±5% (0.05) to ±10% (0.10). Smaller values require larger samples.

Q4: Does this account for disease prevalence?
A: No, this calculates the number of disease-positive cases needed. Total sample size would be N/prevalence.

Q5: What if my expected sensitivity is very high?
A: For sensitivities >90%, you may need very large samples to achieve narrow confidence intervals.