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Mostreig bola de neu ponderat×Mostreig adaptatiu de boles de neu×
CampMetodologia d'enquestesMetodologia d'enquestes
FamíliaProcess / pipelineProcess / pipeline
Any d'origen19971990s–2000s (as combined approach)
Autor originalDouglas D. Heckathorn (formal probability-weighted variant)Combines principles from S. K. Thompson (adaptive sampling, 1990) and L. A. Goodman (snowball sampling, 1961)
TipusProbability-adjusted chain-referral samplingNon-probability / adaptive sampling design
Font seminalHeckathorn, 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 ↗
Àliesweight-adjusted chain-referral sampling, probability-weighted snowball sampling, WSS, weighted referral samplingadaptive referral sampling, adaptive chain-referral sampling, dynamic snowball sampling
Relacionats54
ResumWeighted 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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ScholarGateCompara mètodes: Weighted Snowball Sampling · Adaptive Snowball Sampling. Recuperat el 2026-06-18 de https://scholargate.app/ca/compare