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| 가중 스노우볼 샘플링× | 적응형 스노우볼 샘플링× | |
|---|---|---|
| 분야 | 조사방법론 | 조사방법론 |
| 계열 | Process / pipeline | Process / pipeline |
| 기원 연도≠ | 1997 | 1990s–2000s (as combined approach) |
| 창시자≠ | Douglas D. Heckathorn (formal probability-weighted variant) | Combines principles from S. K. Thompson (adaptive sampling, 1990) and L. A. Goodman (snowball sampling, 1961) |
| 유형≠ | Probability-adjusted chain-referral sampling | Non-probability / adaptive sampling design |
| 원전≠ | Heckathorn, D. D. (1997). Respondent-driven sampling: A new approach to the study of hidden populations. Social Problems, 44(2), 174–199. DOI ↗ | Thompson, S. K. (1990). Adaptive cluster sampling. Journal of the American Statistical Association, 85(412), 1050–1059. DOI ↗ |
| 별칭≠ | weight-adjusted chain-referral sampling, probability-weighted snowball sampling, WSS, weighted referral sampling | adaptive referral sampling, adaptive chain-referral sampling, dynamic snowball sampling |
| 관련≠ | 5 | 4 |
| 요약≠ | Weighted snowball sampling is a chain-referral technique in which participants recruit peers from a hidden or hard-to-reach population, and differential inclusion probabilities are estimated and corrected through statistical weights. Unlike basic snowball sampling, the weighting step allows approximately unbiased population estimates, bridging the gap between convenience-driven recruitment and probability-based inference. | Adaptive snowball sampling is a hybrid sampling strategy that recruits initial participants (seeds) from a target population and then dynamically adjusts referral chains based on pre-specified criteria — such as population density, diversity, or theoretical saturation. Combining the chain-referral logic of snowball sampling with the responsive decision rules of adaptive sampling, it is particularly suited to studying rare, hidden, or hard-to-reach populations where conventional frames are unavailable. |
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