Сравнение методов

	Взвешенная снежная выборка	Адаптивная выборка типа снежный ком
Область	Методология опросов	Методология опросов
Семейство	Process / pipeline	Process / pipeline
Год появления	1997	1990s–2000s (as combined approach)
Автор метода	Douglas D. Heckathorn (formal probability-weighted variant)	Combines principles from S. K. Thompson (adaptive sampling, 1990) and L. A. Goodman (snowball sampling, 1961)
Тип	Probability-adjusted chain-referral sampling	Non-probability / adaptive sampling design
Основополагающий источник	Heckathorn, D. D. (1997). Respondent-driven sampling: A new approach to the study of hidden populations. Social Problems, 44(2), 174–199.	Thompson, S. K. (1990). Adaptive cluster sampling. Journal of the American Statistical Association, 85(412), 1050–1059.
Другие названия	weight-adjusted chain-referral sampling, probability-weighted snowball sampling, WSS, weighted referral sampling	adaptive referral sampling, adaptive chain-referral sampling, dynamic snowball sampling
Связанные	5	4
Сводка	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.