Сравнение на методи

	Многостепенно извадково подбиране с максимална вариация	Многостепенно целенасочено извадково изследване
Област	Методология на проучванията	Методология на проучванията
Семейство	Process / pipeline	Process / pipeline
Година на възникване	1990s–2000s	1980s–1990s
Създател	Synthesized from Patton's maximum variation sampling (1990) and multi-level survey design traditions	Derived from Patton's purposive sampling framework; formalized in multi-site qualitative and mixed-methods research
Тип	Purposive qualitative/mixed-methods sampling design	Non-probability sampling strategy
Основополагащ източник	Patton, M. Q. (2002). Qualitative Research and Evaluation Methods (3rd ed.). Sage. [Chapter 5: Maximum variation sampling and purposeful sampling strategies] ISBN: 978-0761919711	Patton, M. Q. (2002). Qualitative Research and Evaluation Methods (3rd ed.). Sage. ISBN: 978-0761919711
Други названия	hierarchical maximum variation sampling, nested maximum diversity sampling, multi-tier purposive variation sampling, MLMVS	hierarchical purposive sampling, nested purposive sampling, multi-tier purposive sampling, multi-site purposive sampling
Свързани	5	5
Резюме	Multi-level maximum variation sampling is a purposive strategy that deliberately selects cases at two or more nested organizational levels — such as schools within districts, or patients within clinics — while maximizing heterogeneity on key dimensions at each level. The aim is to capture the full range of variation within a hierarchically structured population so that patterns common across diverse contexts can be identified and context-specific differences can be documented with credibility.	Multi-level purposive sampling applies purposive selection criteria at two or more nested levels of a research hierarchy — for instance, first selecting sites or organizations, then selecting participants within each site. This layered approach allows researchers to align the theoretical logic of purposive sampling with the real-world structure of complex, hierarchical populations, making it especially valuable in multi-site qualitative studies and mixed-methods research.