Community Survey Cluster Size Calculator

Work out community survey cluster size instantly with clear inputs, formula shown and shareable results.

About Community Survey Cluster Size Calculator

Calculates the simple random sample size for a proportion, inflates it by the design effect and divides by the cluster size to give the number of clusters.

Formula

Cluster sample size

n = 1.96^2 x p(1-p) / d^2, multiplied by the design effect; clusters = n / cluster size

Worked example

With the default values below, Community Survey Cluster Size Calculator returns Sample size required of 645. Change any input above and every figure here is recalculated in your browser.

Inputs used

Expected prevalenceaccepts 1–99: 30
Margin of erroraccepts 0.5–20: 5
Design effectaccepts 1–6: 2
Households or people per clusteraccepts 5–200: 30

Results

Sample size required: 645
Simple random sample equivalent: 323
Clusters required: 21.51
Clusters to select: 22

Step by step

1Values used
2Cluster sample size
3Sample size required= 645
4Simple random sample equivalent= 323
5Clusters required= 21.51
6Clusters to select= 22

Assumptions and limits

The result is derived only from the 4 inputs listed above. Anything not among them is not part of the calculation.
In particular, this calculator does not take inflation, tax, fees or charges or compounding frequency into account.
Figures are rounded for display to 2 decimal places, so totals built from several rounded parts can differ slightly from the unrounded arithmetic.

How these calculators are built and tested is described on the Methodology page. If a figure looks wrong, please report it.

Frequently Asked Questions

What is a design effect?

The variance inflation caused by clustering; 1.5 to 2 is typical for household surveys of health indicators.

Why 30 clusters?

The classic EPI cluster survey used 30 clusters of 7, which balances precision against field logistics.