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Flernivåklusterurval×Stratifierad stickprovsdragning×
ÄmnesområdeSurveymetodikSurveymetodik
FamiljProcess / pipelineProcess / pipeline
Ursprungsår1950s-1970s (cluster sampling); multilevel extension formalized 1980s-1990s1977
UpphovspersonW. G. Cochran (cluster sampling foundations); extended into multilevel contexts by survey methodologistsWilliam G. Cochran
TypProbability sampling designProbability-based survey sampling design
UrsprungskällaCochran, W. G. (1977). Sampling Techniques (3rd ed.). Wiley. ISBN: 978-0471162407Cochran, W. G. (1977). Sampling Techniques (3rd ed.). Wiley. ISBN: 978-0-471-16240-7
Aliashierarchical cluster sampling, nested cluster sampling, multi-stage cluster sampling, clustered multilevel samplingProportional Stratified Sampling, Optimal Allocation Sampling, Stratum-Based Sampling, Tabakalı Örnekleme
Närliggande62
SammanfattningMulti-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.Stratified sampling is a probability sampling design in which the target population is partitioned into non-overlapping, exhaustive subgroups called strata, and independent probability samples are drawn within each stratum. Formalized by William G. Cochran in Sampling Techniques (1977), the method exploits known population structure to reduce variance and guarantee representativeness of all major subgroups, making it a cornerstone of large-scale survey research and official statistics.
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ScholarGateJämför metoder: Multi-level Cluster Sampling · Stratified Sampling. Hämtad 2026-06-15 från https://scholargate.app/sv/compare