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Адаптивно максимално вариационно подбиране×Максимално вариативно подбиране×
ОбластМетодология на проучваниятаМетодология на проучванията
СемействоProcess / pipelineProcess / pipeline
Година на възникване1990s–2000s (practice codified in qualitative methods literature)1985 (Lincoln & Guba); elaborated 1990–2002 (Patton)
СъздателSynthesizes Patton (maximum variation) and Thompson (adaptive sampling)Lincoln & Guba; systematised by Michael Quinn Patton
ТипAdaptive purposive qualitative sampling strategyPurposive qualitative sampling strategy
Основополагащ източникPatton, M. Q. (1990). Qualitative Evaluation and Research Methods (2nd ed.). Sage. [Maximum variation sampling, pp. 169–183] ISBN: 978-0803937796Patton, M. Q. (2002). Qualitative Research and Evaluation Methods (3rd ed.). Sage. Chapter 5: Purposeful Sampling. ISBN: 978-0761919711
Други названияadaptive purposive maximum variation sampling, iterative maximum variation sampling, adaptive heterogeneous sampling, AMVSmaximum variation sampling, maximum diversity sampling, MVS, heterogeneous sampling
Свързани55
РезюмеAdaptive maximum variation sampling is a purposive qualitative sampling strategy that combines the logic of maximum variation sampling — deliberately selecting cases that differ as widely as possible on key dimensions — with an adaptive, iterative recruitment process. Rather than fixing the full sample in advance, the researcher continuously reviews emerging data to identify which types of cases are underrepresented and recruits new participants to fill those gaps, maximizing heterogeneity throughout data collection.Maximum variation sampling is a purposive qualitative sampling strategy in which the researcher deliberately selects cases that span the widest possible range of variation on dimensions central to the study. The goal is not statistical representation but the identification of common patterns that cut across diverse cases as well as the documentation of the unique ways each context shapes the phenomenon under investigation.
ScholarGateНабор от данни
  1. v1
  2. 2 Източници
  3. PUBLISHED
  1. v1
  2. 2 Източници
  3. PUBLISHED

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ScholarGateСравнение на методи: Adaptive Maximum Variation Sampling · Maximum Variation Sampling. Извлечено на 2026-06-15 от https://scholargate.app/bg/compare