Módszerek összehasonlítása

	Adaptív maximális variációs mintavétel	Célzott mintavétel
Tudományterület	Kérdőíves felmérések módszertana	Kérdőíves felmérések módszertana
Módszercsalád	Process / pipeline	Process / pipeline
Keletkezés éve	1990s–2000s (practice codified in qualitative methods literature)	Formalized ~1980–1990
Megalkotó	Synthesizes Patton (maximum variation) and Thompson (adaptive sampling)	Michael Quinn Patton (systematic articulation); roots in early qualitative inquiry
Típus	Adaptive purposive qualitative sampling strategy	Non-probability sampling strategy
Alapmű	Patton, M. Q. (1990). Qualitative Evaluation and Research Methods (2nd ed.). Sage. [Maximum variation sampling, pp. 169–183] ISBN: 978-0803937796	Patton, M. Q. (1990). Qualitative Evaluation and Research Methods (2nd ed.). Sage. ISBN: 978-0803937796
Alternatív nevek	adaptive purposive maximum variation sampling, iterative maximum variation sampling, adaptive heterogeneous sampling, AMVS	judgmental sampling, selective sampling, criterion-based sampling, purposeful sampling
Kapcsolódó	5	4
Összefoglaló	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.	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.