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Adaptív Hólabda Mintavétel×Hólabda-módszer×
TudományterületKérdőíves felmérések módszertanaKérdőíves felmérések módszertana
MódszercsaládProcess / pipelineProcess / pipeline
Keletkezés éve1990s–2000s (as combined approach)1961
MegalkotóCombines principles from S. K. Thompson (adaptive sampling, 1990) and L. A. Goodman (snowball sampling, 1961)Leo A. Goodman
TípusNon-probability / adaptive sampling designNon-probability sampling technique
AlapműThompson, S. K. (1990). Adaptive cluster sampling. Journal of the American Statistical Association, 85(412), 1050–1059. DOI ↗Goodman, L. A. (1961). Snowball sampling. Annals of Mathematical Statistics, 32(1), 148–170. DOI ↗
Alternatív nevekadaptive referral sampling, adaptive chain-referral sampling, dynamic snowball samplingchain-referral sampling, network sampling, respondent-driven sampling, referral sampling
Kapcsolódó43
ÖsszefoglalóAdaptive 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.Snowball sampling is a non-probability recruitment technique in which initial participants (seeds) refer the researcher to others who meet the study criteria, and those referrals in turn refer further participants. The sample grows incrementally — like a rolling snowball — until the required size or theoretical saturation is reached. It is the method of choice when a target population has no accessible sampling frame, such as undocumented migrants, illicit drug users, survivors of stigmatised experiences, or members of closed professional networks.
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ScholarGateMódszerek összehasonlítása: Adaptive Snowball Sampling · Snowball Sampling. Letöltve 2026-06-17, forrás: https://scholargate.app/hu/compare