방법 비교
선택한 방법을 나란히 검토하세요. 서로 다른 행은 강조 표시됩니다.
| 적응형 다단계 표본 추출× | 체계적 표본 추출× | |
|---|---|---|
| 분야 | 조사방법론 | 조사방법론 |
| 계열 | Process / pipeline | Process / pipeline |
| 기원 연도≠ | 1977 (multistage base); 1990-1992 (adaptive extensions by Thompson) | Mid-20th century (Cochran 1953; Kish 1965) |
| 창시자≠ | Steven K. Thompson (adaptive principles); William G. Cochran (multistage framework) | William G. Cochran; formalized in survey sampling theory |
| 유형≠ | Probability-based adaptive sampling design | Probability sampling design |
| 원전≠ | Thompson, S. K. (1992). Sampling. Wiley. ISBN: 978-0471548850 | Cochran, W. G. (1977). Sampling Techniques (3rd ed.). John Wiley & Sons. ISBN: 978-0471162407 |
| 별칭 | AMS, adaptive multi-phase sampling, sequential multistage sampling, adaptive hierarchical sampling | interval sampling, systematic random sampling, equal-interval sampling, fixed-interval sampling |
| 관련 | 5 | 5 |
| 요약≠ | Adaptive multistage sampling combines the hierarchical efficiency of multistage designs with adaptive decision rules that adjust which units are sampled at later stages based on what is observed at earlier stages. It is used when a target characteristic is rare, clustered, or spatially heterogeneous and a fixed design would waste resources on uninformative areas of the population. | 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. |
| ScholarGate데이터셋 ↗ |
|
|