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Целенаправленная выборка×Метод отбора респондентов по назначению (Respondent-Driven Sampling, RDS)×
ОбластьМетодология опросовМетодология опросов
СемействоProcess / pipelineProcess / pipeline
Год появленияFormalized ~1980–19901997
Автор методаMichael Quinn Patton (systematic articulation); roots in early qualitative inquiryDouglas Heckathorn
ТипNon-probability sampling strategyProbabilistic chain-referral sampling design
Основополагающий источникPatton, M. Q. (1990). Qualitative Evaluation and Research Methods (2nd ed.). Sage. ISBN: 978-0803937796Heckathorn, D. D. (1997). Respondent-driven sampling: A new approach to the study of hidden populations. Social Problems, 44(2), 174–199. DOI ↗
Другие названияjudgmental sampling, selective sampling, criterion-based sampling, purposeful samplingChain-Referral Sampling, Peer-Referral Sampling, Network-Based Sampling, Katılımcı Güdümlü Örnekleme
Связанные43
СводкаPurposive 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.Respondent-Driven Sampling (RDS) is a probabilistic chain-referral method designed to reach hidden or hard-to-reach populations that lack a sampling frame. Introduced by sociologist Douglas Heckathorn in 1997, RDS combines snowball recruitment with mathematical weighting based on participants' personal network sizes, allowing researchers to generate population-level estimates even when no complete membership list exists.
ScholarGateНабор данных
  1. v1
  2. 2 Источники
  3. PUBLISHED
  1. v1
  2. 1 Источники
  3. PUBLISHED

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ScholarGateСравнение методов: Purposive sampling · Respondent-Driven Sampling. Получено 2026-06-17 из https://scholargate.app/ru/compare