Adaptive Snowball Sampling
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.
Source record
Citations copied verbatim from the method’s source record. No claim-level verification is inferred from them.
- Thompson, S. K. (1990). Adaptive cluster sampling. Journal of the American Statistical Association, 85(412), 1050–1059. · DOI 10.1080/01621459.1990.10474975
- Goodman, L. A. (1961). Snowball sampling. The Annals of Mathematical Statistics, 32(1), 148–170. · DOI 10.1214/aoms/1177705148
Curated claims
Claims persisted in the evidence ledger, each with its own assessment.
This view does not invent a claim assessment when the ledger has none.
Related methods
Generated from the method graph and shown as machine-suggested relations — no evidence claim is inferred.