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Persampelan Bola Salji Adaptif×Pemilihan Sampel Bertujuan×
BidangMetodologi TinjauanMetodologi Tinjauan
KeluargaProcess / pipelineProcess / pipeline
Tahun asal1990s–2000s (as combined approach)Formalized ~1980–1990
PengasasCombines principles from S. K. Thompson (adaptive sampling, 1990) and L. A. Goodman (snowball sampling, 1961)Michael Quinn Patton (systematic articulation); roots in early qualitative inquiry
JenisNon-probability / adaptive sampling designNon-probability sampling strategy
Sumber perintisThompson, S. K. (1990). Adaptive cluster sampling. Journal of the American Statistical Association, 85(412), 1050–1059. DOI ↗Patton, M. Q. (1990). Qualitative Evaluation and Research Methods (2nd ed.). Sage. ISBN: 978-0803937796
Aliasadaptive referral sampling, adaptive chain-referral sampling, dynamic snowball samplingjudgmental sampling, selective sampling, criterion-based sampling, purposeful sampling
Berkaitan44
RingkasanAdaptive 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.Purposive sampling is a non-probability strategy in which the researcher deliberately selects participants, documents, or cases that are information-rich with respect to the research question. Rather than drawing units at random, the researcher applies explicit criteria aligned with the study's purpose, maximising the depth and relevance of the data collected. It is the default sampling logic in most qualitative research designs and is also used in mixed-methods and applied evaluative work.
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ScholarGateBandingkan kaedah: Adaptive Snowball Sampling · Purposive sampling. Dicapai 2026-06-17 daripada https://scholargate.app/ms/compare