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| 적응형 층화 표본 추출× | 체계적 표본 추출× | |
|---|---|---|
| 분야 | 조사방법론 | 조사방법론 |
| 계열 | Process / pipeline | Process / pipeline |
| 기원 연도≠ | 1990s (formal development from Thompson 1990 onward) | Mid-20th century (Cochran 1953; Kish 1965) |
| 창시자≠ | Steven K. Thompson (adaptive sampling); allocation adaptations by Salehi, Seber, and others | William G. Cochran; formalized in survey sampling theory |
| 유형≠ | Probability-based adaptive sampling design | Probability sampling design |
| 원전≠ | Thompson, S. K. (1990). Adaptive cluster sampling. Journal of the American Statistical Association, 85(412), 1050–1059. DOI ↗ | Cochran, W. G. (1977). Sampling Techniques (3rd ed.). John Wiley & Sons. ISBN: 978-0471162407 |
| 별칭 | ASS, adaptive stratified design, stratified adaptive sampling, adaptive allocation stratified sampling | interval sampling, systematic random sampling, equal-interval sampling, fixed-interval sampling |
| 관련≠ | 6 | 5 |
| 요약≠ | Adaptive stratified sampling divides the population into strata and then applies an adaptive rule within each stratum: whenever an initially selected unit satisfies a pre-specified condition (e.g., a rare species is found, a variable exceeds a threshold), neighboring or related units are added to the sample. This combines the variance-reduction power of stratification with the ability to concentrate sampling effort where the phenomenon of interest is actually present. | 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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