Порівняння методів

	Кількісно-домінантний змішаний метод, орієнтований на випадок	Багаторівневий дизайн зі змішаними методами
Галузь	Дизайн дослідження	Дизайн дослідження
Родина	Process / pipeline	Process / pipeline
Рік появи	2003–2007	Late 1990s–2000s
Автор методу	Tashakkori & Teddlie (dominant-status typology); Creswell & Plano Clark (design taxonomy)	Bonnie Nastasi, John Hitchcock, and collaborators; systematized by Creswell & Plano Clark
Тип	Mixed methods research design	Mixed methods research design
Основоположне джерело	Tashakkori, A., & Teddlie, C. (Eds.). (2010). SAGE Handbook of Mixed Methods in Social and Behavioral Research (2nd ed.). Sage. ISBN: 978-1412972666	Creswell, J. W., & Plano Clark, V. L. (2018). Designing and Conducting Mixed Methods Research (3rd ed.). Sage Publications. ISBN: 978-1483357829
Інші назви	QUAN-dominant case study MMR, quantitatively weighted case mixed methods, dominant-status case-centered mixed design	multilevel MMR, nested mixed methods, hierarchical mixed methods design, cross-level mixed methods
Пов'язані	6	5
Підсумок	Quantitative-dominant case-focused mixed methods organizes a study around one or more clearly bounded cases while assigning primary weight and inferential authority to quantitative data. Qualitative data are collected within the same case boundaries and serve an augmenting, explanatory, or contextual role rather than an equal one. The design is ideal when a case (a school, organization, community, or patient cohort) is the unit of analysis and the core research questions require measurable outcomes that qualitative evidence then helps interpret or explain.	Multilevel mixed methods design is a research approach that collects and integrates both quantitative and qualitative data at two or more distinct levels of a social or organizational hierarchy — for example, individuals nested within classrooms, classrooms within schools, or patients within healthcare teams. By pairing quantitative measurement of outcomes at one level with qualitative exploration of meaning at another, researchers gain a richer, more complete picture than either strand alone could provide.