Сравнение методов

	Кластерная выборка с непропорциональным распределением	Многоступенчатая выборка
Область	Методология опросов	Методология опросов
Семейство	Process / pipeline	Process / pipeline
Год появления	Mid-20th century (formalised 1950s–1965)	1950s–1960s (formalized in Kish 1965 and Cochran 1977)
Автор метода	Leslie Kish; William G. Cochran	Leslie Kish; William G. Cochran
Тип	Probability sampling design	Probability sampling design
Основополагающий источник	Kish, L. (1965). Survey Sampling. John Wiley & Sons. ISBN: 978-0471489009	Kish, L. (1965). Survey Sampling. John Wiley & Sons. ISBN: 978-0471109495
Другие названия	disproportionate cluster sampling, unequal-probability cluster sampling, variable-rate cluster sampling, non-proportional cluster sampling	multistage cluster sampling, multi-stage sampling, nested sampling, hierarchical 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.	Multistage sampling is a probability-based design that selects a sample by working through two or more successive levels of a population hierarchy — for example, first selecting regions, then districts within those regions, then households within those districts. It makes large-scale surveys practical when a complete population list is unavailable or when the population is geographically dispersed, by concentrating fieldwork within a manageable number of sampled units at each stage.