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Adaptiv klusterdragning – ACS×Snöbollsurval×
ÄmnesområdeSurveymetodikSurveymetodik
FamiljProcess / pipelineProcess / pipeline
Ursprungsår19901961
UpphovspersonSteven K. ThompsonLeo A. Goodman
TypProbability-based adaptive sampling designNon-probability sampling technique
UrsprungskällaThompson, 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 ↗
AliasACS, adaptive network sampling, sequential cluster sampling, neighborhood adaptive samplingchain-referral sampling, network sampling, respondent-driven sampling, referral sampling
Närliggande63
SammanfattningAdaptive cluster sampling (ACS) is a probability-based design in which an initial random sample of units triggers the inclusion of neighboring units whenever a predefined condition — typically a threshold count of a rare attribute — is satisfied. Developed by Steven K. Thompson in 1990, ACS is especially powerful for estimating the abundance or distribution of rare, spatially clustered populations such as endangered species, disease hotspots, or hard-to-reach social groups.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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ScholarGateJämför metoder: Adaptive Cluster Sampling · Snowball Sampling. Hämtad 2026-06-15 från https://scholargate.app/sv/compare