Stratified cluster sampling framework

A stratified cluster sampling framework brings together both cluster and stratifying sampling techniques. Cluster sampling is a term used to describe probability sampling where a population is split into smaller groups called clusters and people are picked at random from these clusters to make a sample. Cluster sampling is typically used with large, geographically spread-out populations. A stratified sample is a representational sample of a population that is acquired by splitting a population into homogeneous sub-groups called strata. Each stratum consists of people with similar characteristics in terms of income, race, sex, or educational attainment, among other factors. This sampling method can be used to ensure adequate representation from particular groups, for example, those from disadvantaged areas or ethnic minority groups.