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| 비례 다단계 표본 추출× | 체계적 표본 추출× | |
|---|---|---|
| 분야 | 조사방법론 | 조사방법론 |
| 계열 | Process / pipeline | Process / pipeline |
| 기원 연도≠ | 1950s–1960s | Mid-20th century (Cochran 1953; Kish 1965) |
| 창시자≠ | Leslie Kish; William G. Cochran (theoretical foundations) | William G. Cochran; formalized in survey sampling theory |
| 유형 | Probability sampling design | Probability sampling design |
| 원전≠ | Kish, L. (1965). Survey Sampling. John Wiley & Sons. (Chapters 6–7 on multistage and PPS designs.) ISBN: 978-0471489009 | Cochran, W. G. (1977). Sampling Techniques (3rd ed.). John Wiley & Sons. ISBN: 978-0471162407 |
| 별칭 | proportional PPS multistage sampling, multistage probability proportional to size sampling, proportionate multistage cluster sampling, PPS multistage sampling | interval sampling, systematic random sampling, equal-interval sampling, fixed-interval sampling |
| 관련≠ | 6 | 5 |
| 요약≠ | Proportional multistage sampling is a probability sampling design that selects units across two or more hierarchical stages — for example, regions, then districts, then households — where the number of units drawn at each stage is proportional to the size of each higher-level unit. By weighting selection probabilities to match cluster size, it produces self-weighting samples that closely mirror the population structure and simplify variance estimation. | Systematic sampling is a probability sampling technique in which every k-th element is selected from an ordered list of the population after a random starting point. With population size N and desired sample size n, the sampling interval k = N/n is computed and one unit is chosen at random from the first interval; all subsequent units are selected by adding k repeatedly. The method is operationally simple, yields a spread-out sample, and often achieves lower variance than simple random sampling when the list has no harmful periodicity. |
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