DEFF efeito desenho
- Created by
- Renato Passos, Eng. de Software
- Reviewed by
- Renato Passos, Eng. de Software
Last updated: Apr 18, 2026
About this calculator
The DEFF (Design Effect) calculator is used in cluster sampling to adjust sample size requirements, accounting for the loss of precision due to intra-cluster correlations. The formula 1 + (m−1)·ρ calculates the inflation factor, where m is the average cluster size and ρ is the intra-class correlation coefficient.
This tool is critical in studies dividing populations into groups (e.g., schools, neighborhoods, or families) and randomly sampling within them. DEFF corrects the estimate's variance, ensuring the sample size is adequate to achieve statistically significant results despite the cluster structure.
Use this calculator when cluster sampling might increase data variability. Examples include public health or education research, where individuals in the same cluster share similar traits. The output prevents underestimating standard errors, a common issue in non-random cluster sampling.
Cautions: Ensure accurate m and ρ values, based on pilot data or relevant literature. Errors in these parameters can lead to imprecise calculations, undermining the sample's validity and statistical inference.
Frequently asked questions
What does DEFF measure in cluster sampling?
DEFF measures how much data variability increases when cluster sampling is used compared to simple random sampling.
How is the formula 1 + (m−1)·ρ applied in practice?
The formula multiplies the intra-class correlation coefficient (ρ) by the average group size (m−1) and adds 1. The result adjusts the required sample size to achieve desired precision.
When should I use this calculator in a study?
Use it when your sampling involves groups (clusters) and there's correlation between elements within the same group, such as in community or school-based surveys.
What happens if ρ is zero?
If ρ is zero, DEFF becomes 1, indicating cluster sampling doesn't affect variance. This occurs when elements within clusters are statistically independent.
How to obtain m and ρ values for the calculation?
m is estimated from the average cluster size in the population. ρ can be calculated with pilot data or adapted from similar studies in the same research area.