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Linganisha mbinu

Pitia mbinu ulizochagua bega kwa bega; safu zinazotofautiana zinaangaziwa.

Usampulishaji wa Tofauti Upeo Unaojirekebisha×Uchanganuzi wa Kiwango cha Juu cha Utatanishi×
NyanjaMetodolojia ya DodosoMetodolojia ya Dodoso
FamiliaProcess / pipelineProcess / pipeline
Mwaka wa asili1990s–2000s (practice codified in qualitative methods literature)1985 (Lincoln & Guba); elaborated 1990–2002 (Patton)
MwanzilishiSynthesizes Patton (maximum variation) and Thompson (adaptive sampling)Lincoln & Guba; systematised by Michael Quinn Patton
AinaAdaptive purposive qualitative sampling strategyPurposive qualitative sampling strategy
Chanzo asiliaPatton, 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
Majina mbadalaadaptive purposive maximum variation sampling, iterative maximum variation sampling, adaptive heterogeneous sampling, AMVSmaximum variation sampling, maximum diversity sampling, MVS, heterogeneous sampling
Zinazohusiana55
MuhtasariAdaptive 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.
ScholarGateSeti ya data
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  1. v1
  2. 2 Vyanzo
  3. PUBLISHED

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