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অভিযোজিত স্নোবল স্যাম্পলিং×উদ্দেশ্যমূলক নমুনায়ন×
ক্ষেত্রজরিপ পদ্ধতিজরিপ পদ্ধতি
পরিবারProcess / pipelineProcess / pipeline
উদ্ভবের বছর1990s–2000s (as combined approach)Formalized ~1980–1990
প্রবর্তকCombines 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
ধরনNon-probability / adaptive sampling designNon-probability sampling strategy
মৌলিক উৎসThompson, 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
অপর নামadaptive referral sampling, adaptive chain-referral sampling, dynamic snowball samplingjudgmental sampling, selective sampling, criterion-based sampling, purposeful sampling
সম্পর্কিত44
সারসংক্ষেপAdaptive 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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ScholarGateপদ্ধতির তুলনা করুন: Adaptive Snowball Sampling · Purposive sampling. 2026-06-17 তারিখে সংগৃহীত, উৎস: https://scholargate.app/bn/compare