Сравнение методов

	Кластерная выборка с непропорциональным распределением	Кластерная выборка
Область	Методология опросов	Методология опросов
Семейство	Process / pipeline	Process / pipeline
Год появления	Mid-20th century (formalised 1950s–1965)	Early-to-mid 20th century; canonical treatment 1953/1977
Автор метода	Leslie Kish; William G. Cochran	Formalized by William G. Cochran; roots in early 20th-century U.S. Census Bureau survey practice
Тип	Probability sampling design	Probability sampling design
Основополагающий источник	Kish, L. (1965). Survey Sampling. John Wiley & Sons. ISBN: 978-0471489009	Cochran, W. G. (1977). Sampling Techniques (3rd ed.). Wiley. ISBN: 978-0471162407
Другие названия	disproportionate cluster sampling, unequal-probability cluster sampling, variable-rate cluster sampling, non-proportional cluster sampling	cluster random sampling, area sampling, one-stage cluster sampling
Связанные	6	5
Сводка	Disproportional cluster sampling is a probability-based survey design in which naturally occurring groups (clusters) are selected as primary sampling units, but the number of clusters or elements drawn from each group is not proportional to that group's share of the population. By deliberately over- or under-sampling certain clusters, researchers gain analytic flexibility and precision where it matters most, at the cost of requiring post-hoc weighting for population-level inference.	Cluster sampling is a probability sampling technique in which the population is divided into naturally occurring groups (clusters), a random sample of clusters is selected, and all — or a random subset of — members within each selected cluster are studied. It is especially practical when a complete population list is unavailable or when units are geographically dispersed, making individual random selection prohibitively expensive. One-stage cluster sampling surveys every member of selected clusters; two-stage designs add a second random draw within clusters.