1. What is the Raosoft Sample Size Formula?

The Raosoft sample size formula calculates the minimum number of participants needed to estimate a population prevalence with a specified confidence level and precision. It's commonly used in epidemiological studies and survey research.

2. How Does the Calculator Work?

The calculator uses the Raosoft formula:

Where:

• \( n \) — Required sample size
• \( Z \) — Z-score for desired confidence level
• \( p \) — Expected prevalence (proportion)
• \( d \) — Desired precision (margin of error)

Explanation: The formula accounts for the relationship between confidence level, expected prevalence, and desired precision to determine the minimum sample size needed.

3. Importance of Sample Size Calculation

Details: Proper sample size calculation ensures studies have adequate power to detect effects while avoiding unnecessary resource expenditure. Underpowered studies may miss important findings, while oversized studies waste resources.

4. Using the Calculator

Tips:

• For unknown prevalence, use p = 0.5 (most conservative estimate)
• Common precision values are 0.05 (5%) or 0.03 (3%)
• 95% confidence (Z=1.96) is standard for most studies

5. Frequently Asked Questions (FAQ)

Q1: Why use p=0.5 when prevalence is unknown?
A: p=0.5 gives the maximum sample size (most conservative estimate) since p(1-p) is maximized at p=0.5.

Q2: How does precision affect sample size?
A: Sample size increases quadratically as precision improves (halving precision requires 4× the sample size).

Q3: What's the difference between 95% and 99% confidence?
A: 99% confidence (Z=2.576) requires about 73% more participants than 95% confidence (Z=1.96) for the same precision.

Q4: When should I use finite population correction?
A: When sampling >5% of a finite population. This calculator provides the infinite population estimate.

Q5: Can this be used for non-prevalence studies?
A: This formula is specific for prevalence estimation. Different formulas exist for means, proportions, etc.