Порівняння методів

	Багаторівневий кластерний відбір	Кластерна вибірка
Галузь	Методологія опитувань	Методологія опитувань
Родина	Process / pipeline	Process / pipeline
Рік появи	1950s-1970s (cluster sampling); multilevel extension formalized 1980s-1990s	Early-to-mid 20th century; canonical treatment 1953/1977
Автор методу	W. G. Cochran (cluster sampling foundations); extended into multilevel contexts by survey methodologists	Formalized by William G. Cochran; roots in early 20th-century U.S. Census Bureau survey practice
Тип	Probability sampling design	Probability sampling design
Основоположне джерело	Cochran, W. G. (1977). Sampling Techniques (3rd ed.). Wiley. ISBN: 978-0471162407	Cochran, W. G. (1977). Sampling Techniques (3rd ed.). Wiley. ISBN: 978-0471162407
Інші назви	hierarchical cluster sampling, nested cluster sampling, multi-stage cluster sampling, clustered multilevel sampling	cluster random sampling, area sampling, one-stage cluster sampling
Пов'язані	6	5
Підсумок	Multi-level cluster sampling is a probability sampling design for hierarchically structured populations — such as students nested within classrooms within schools within districts. Clusters are randomly selected at each level of the hierarchy before individual units are sampled within the final-level clusters. The design mirrors the natural nesting of real-world populations and enables efficient large-scale data collection while supporting multilevel statistical analysis.	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.