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Disproportional Stratified Sampling×Flerstegsutv"al - Flerstegs klusterurval×
ÄmnesområdeSurveymetodikSurveymetodik
FamiljProcess / pipelineProcess / pipeline
Ursprungsår19341950s–1960s (formalized in Kish 1965 and Cochran 1977)
UpphovspersonJerzy NeymanLeslie Kish; William G. Cochran
TypProbability sampling designProbability sampling design
UrsprungskällaCochran, W. G. (1977). Sampling Techniques (3rd ed.). John Wiley & Sons. ISBN: 978-0471162407Kish, L. (1965). Survey Sampling. John Wiley & Sons. ISBN: 978-0471109495
Aliasdisproportionate stratified sampling, unequal-probability stratified sampling, oversampling stratified design, non-proportional stratified samplingmultistage cluster sampling, multi-stage sampling, nested sampling, hierarchical sampling
Närliggande65
SammanfattningDisproportional stratified sampling divides the population into mutually exclusive strata and deliberately draws different proportions from each stratum — oversampling small or analytically important subgroups and undersampling large ones. Post-hoc weighting restores population-level representativeness when overall estimates are needed. First formalised by Jerzy Neyman in 1934, it is the standard approach when subgroup-level precision matters as much as total-population estimates.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.
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ScholarGateJämför metoder: Disproportional Stratified Sampling · Multistage Sampling. Hämtad 2026-06-18 från https://scholargate.app/sv/compare