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Lĩnh vựcPhương pháp luận khảo sátPhương pháp luận khảo sát
HọProcess / pipelineProcess / pipeline
Năm ra đời1960s–1980s (developed alongside large-scale survey programs)1977
Người khởi xướngLeslie Kish (probability sampling theory); complex survey methodologistsWilliam G. Cochran
LoạiProbability sampling designProbability-based survey sampling design
Công trình gốcKish, L. (1965). Survey Sampling. John Wiley & Sons. New York. ISBN: 978-0471109495Cochran, W. G. (1977). Sampling Techniques (3rd ed.). Wiley. ISBN: 978-0-471-16240-7
Tên gọi kháchierarchical weighted sampling, nested weighted sampling, multilevel probability weighting, weighted hierarchical samplingProportional Stratified Sampling, Optimal Allocation Sampling, Stratum-Based Sampling, Tabakalı Örnekleme
Liên quan62
Tóm tắtMulti-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.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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ScholarGateSo sánh phương pháp: Multi-level weighted sampling · Stratified Sampling. Truy cập ngày 2026-06-15 từ https://scholargate.app/vi/compare