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Compară metode

Examinează metodele selectate una lângă alta; rândurile care diferă sunt evidențiate.

Eșantionare ponderată multinivel×Eșantionarea pe grupe (Cluster Sampling)×
DomeniuMetodologia anchetelorMetodologia anchetelor
FamilieProcess / pipelineProcess / pipeline
Anul apariției1960s–1980s (developed alongside large-scale survey programs)Early-to-mid 20th century; canonical treatment 1953/1977
Autorul originalLeslie Kish (probability sampling theory); complex survey methodologistsFormalized by William G. Cochran; roots in early 20th-century U.S. Census Bureau survey practice
TipProbability sampling designProbability sampling design
Sursa seminalăKish, L. (1965). Survey Sampling. John Wiley & Sons. New York. ISBN: 978-0471109495Cochran, W. G. (1977). Sampling Techniques (3rd ed.). Wiley. ISBN: 978-0471162407
Denumiri alternativehierarchical weighted sampling, nested weighted sampling, multilevel probability weighting, weighted hierarchical samplingcluster random sampling, area sampling, one-stage cluster sampling
Înrudite65
RezumatMulti-level weighted sampling is a probability-based survey design that draws samples from hierarchically nested populations — such as students within classrooms within schools within districts — and assigns design weights at each level to account for unequal selection probabilities. The resulting weighted data enable unbiased population-level inference despite the complex, non-proportional structure of the sampling frame. It is the backbone of major international assessments such as PISA and TIMSS.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.
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ScholarGateCompară metode: Multi-level weighted sampling · Cluster Sampling. Preluat la 2026-06-15 de pe https://scholargate.app/ro/compare