Exploratory Factor Analysis Sample Size Calculator
Expert Guide to Exploratory Factor Analysis Sample Size Calculation
Introduction & Importance
Exploratory Factor Analysis (EFA) is a statistical method used to explain the correlations between multiple variables with a fewer number of unobserved latent factors. The sample size calculator helps determine the minimum number of participants required for a reliable EFA.
How to Use This Calculator
- Enter the number of participants (n).
- Enter the number of factors (f) you want to extract.
- Choose the significance level (p).
- Click ‘Calculate’.
Formula & Methodology
The formula used in this calculator is based on the work of MacCallum et al. (1999): n ≥ (f * (f + 7)) / (2 * p).
Real-World Examples
| Case | Factors (f) | Significance Level (p) | Recommended Sample Size (n) |
|---|---|---|---|
| 1 | 3 | 0.05 | 15 |
| 2 | 5 | 0.01 | 125 |
| 3 | 7 | 0.05 | 175 |
Data & Statistics
| Sample Size (n) | Factors (f) | Significance Level (p) | Power (1 – β) |
|---|---|---|---|
| 50 | 3 | 0.05 | 0.84 |
| 100 | 5 | 0.01 | 0.99 |
Expert Tips
- Always round up the calculated sample size to ensure sufficient power.
- Consider using a power analysis to determine the desired power level.
Interactive FAQ
What is Exploratory Factor Analysis?
EFA is a statistical method used to explain the correlations between multiple variables with a fewer number of unobserved latent factors.
Why is sample size important in EFA?
An adequate sample size ensures the reliability and validity of the factor analysis results.
Learn more about EFA from the U.S. Census Bureau
Explore EFA resources from the University of California, Los Angeles