Sampling > Multistage Sampling

## What is Multistage Sampling?

Multistage sampling divides large populations into stages to make the sampling process more practical. A combination of stratified sampling or cluster sampling and simple random sampling is usually used.Let’s say you wanted to find out which subjects U.S. school children preferred. A population list — a list of all U.S. schoolchildren– would be near-impossible to come by, so you cannot take a sample of the population. Instead, you divide the population into states and take a simple random sample of states. For the next stage, you might take a simple random sample of schools from within those states. Finally you could perform simple random sampling on the students within the schools to get your sample.

In order to classify multistage sampling as probability sampling, each stage must involve a probability sampling method.

## Real Life Examples

- The
**Census Bureau**uses multistage sampling for the U.S. National Center for

Health Statistics’ National Health Interview Survey (NHIS). A multistage probability sample of 42,000 households in 376 probability sampling units (PSUs are usually counties or groups of counties), which are chosen in groups of around four adjacent households. - The
**Gallup poll**uses multistage sampling. For example, they might randomly choose a certain number of area codes then randomly sample a number of phone numbers from within each area code. - Johnston et. al’s
**survey on drug use in high schools**used three stage sampling: geographic areas, followed by high schools within those areas, followed by senior students in those schools. - The
**Australian Bureau of Statistics**divides cities into “collection districts”, then blocks, then households. Each stage uses random sampling, creating a need to list specific households only after the final stage of sampling.

**Reference**:

Research Methods by Donald H. McBurney, Theresa L. White.

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