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Linganisha mbinu

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Uchaguzi wa Sampuli za Kukuza za Adaptive×Njia ya kukusanya sampuli kwa njia ya mpira wa theluji×
NyanjaMetodolojia ya DodosoMetodolojia ya Dodoso
FamiliaProcess / pipelineProcess / pipeline
Mwaka wa asili19901961
MwanzilishiSteven K. ThompsonLeo A. Goodman
AinaProbability-based adaptive sampling designNon-probability sampling technique
Chanzo asiliaThompson, 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 ↗
Majina mbadalaACS, adaptive network sampling, sequential cluster sampling, neighborhood adaptive samplingchain-referral sampling, network sampling, respondent-driven sampling, referral sampling
Zinazohusiana63
MuhtasariAdaptive 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.
ScholarGateSeti ya data
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  1. v1
  2. 2 Vyanzo
  3. PUBLISHED

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ScholarGateLinganisha mbinu: Adaptive Cluster Sampling · Snowball Sampling. Imepatikana 2026-06-15 kutoka https://scholargate.app/sw/compare