Запис о доказима методе

Adaptive Maximum Variation Sampling

Adaptive 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.

Sources recorded, not reviewed

Изворни запис

Цитирани радови су копирани дословно из изворног записа методе. Из њих се не изводи верификација на нивоу тврдње.

Adaptive Maximum Variation Purposive Sampling

Таксономски запис методе · process-pipeline / survey-methodology

Patton, M. Q. (1990). Qualitative Evaluation and Research Methods (2nd ed.). Sage. [Maximum variation sampling, pp. 169–183] · ISBN 978-0803937796
Thompson, S. K. (1990). Adaptive cluster sampling. Journal of the American Statistical Association, 85(412), 1050–1059. · DOI 10.2307/2289601

Отвори пуну методу

Куроване тврдње

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Још увек нема курованих тврдњи

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Сродне методе

Генерисано из графа метода и приказано као машински предложене везе — не изводи се тврдња доказа.

Taxonomic bucketAdaptive Cluster Samplingmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketAdaptive Stratified Samplingmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketMaximum Variation Samplingmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketPurposive samplingmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketSnowball Samplingmachine-suggested · Relational suggestion, not evidence.