By ToolzHive
About this tool
Sample sizes for prevalence studies, means, proportions, case-control, cohort studies and RCTs.
How to use Sample Size Calculator
- Choose your study design, such as a prevalence survey or a two-group trial.
- Enter the expected proportions or means, confidence level and power.
- Add expected dropout and a design effect for cluster samples, then read the size per group.
Worked example
A prevalence survey expecting 50% with a ±5% margin at 95% confidence needs 385 people; allowing 10% non-response raises it to 428.
What proportion should I use if I do not know it?
Use a figure from earlier studies or a pilot. If there is none, 50% gives the largest and therefore safest sample size.
Why add dropout?
People withdraw, move or fail to respond. Dividing by (1 − dropout rate) keeps enough complete cases for the planned power.
What is the design effect?
Cluster sampling (for example by village or clinic) makes people within a cluster alike, so you need more of them. Multiply by the design effect, often 1.5–2.
Put this guide into practice
- Sample Size Calculator — Sample sizes for prevalence studies, means, proportions, case-control, cohort studies and RCTs.