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| 가중 표본 추출× | 다단계 표본 추출× | |
|---|---|---|
| 분야 | 조사방법론 | 조사방법론 |
| 계열 | Process / pipeline | Process / pipeline |
| 기원 연도≠ | 1940s–1952 (formalized in large-scale government survey work and the Horvitz-Thompson estimator) | 1950s–1960s (formalized in Kish 1965 and Cochran 1977) |
| 창시자≠ | Morris H. Hansen, William N. Hurwitz; D. G. Horvitz and D. J. Thompson (theoretical framework) | Leslie Kish; William G. Cochran |
| 유형 | Probability sampling design | Probability sampling design |
| 원전≠ | Cochran, W. G. (1977). Sampling Techniques (3rd ed.). John Wiley & Sons. ISBN: 978-0471162407 | Kish, L. (1965). Survey Sampling. John Wiley & Sons. ISBN: 978-0471109495 |
| 별칭 | probability proportional to size sampling, PPS sampling, unequal probability sampling, importance sampling | multistage cluster sampling, multi-stage sampling, nested sampling, hierarchical sampling |
| 관련≠ | 6 | 5 |
| 요약≠ | Weighted sampling is a probability-based design in which units are selected with unequal probabilities proportional to a known auxiliary measure of size or importance. Sampling weights — the inverse of inclusion probabilities — are applied during analysis so that each sampled unit correctly represents the population units it stands for. The approach underpins large-scale government, health, and social surveys where simple random sampling would be inefficient. | 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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