Сравнение методов

	Quantitative-dominant explanatory sequential mixed methods	Многоуровневый дизайн смешанных методов
Область	Дизайн исследования	Дизайн исследования
Семейство	Process / pipeline	Process / pipeline
Год появления	2007 (first edition of Designing and Conducting Mixed Methods Research)	Late 1990s–2000s
Автор метода	John W. Creswell & Vicki L. Plano Clark	Bonnie Nastasi, John Hitchcock, and collaborators; systematized by Creswell & Plano Clark
Тип	Mixed methods research design variant	Mixed methods research design
Основополагающий источник	Creswell, J. W., & Plano Clark, V. L. (2018). Designing and Conducting Mixed Methods Research (3rd ed.). Sage. ISBN: 978-1483344379	Creswell, J. W., & Plano Clark, V. L. (2018). Designing and Conducting Mixed Methods Research (3rd ed.). Sage Publications. ISBN: 978-1483357829
Другие названия	QUAN-dominant explanatory sequential design, quan-priority explanatory sequential MMR, quantitative-dominant QUAN→qual design, weighted explanatory sequential mixed methods	multilevel MMR, nested mixed methods, hierarchical mixed methods design, cross-level mixed methods
Связанные	5	5
Сводка	The quantitative-dominant explanatory sequential mixed methods design is a two-phase mixed methods approach in which a larger, primary quantitative study is conducted first, followed by a smaller, secondary qualitative phase that explains, elaborates, or contextualises the quantitative results. Quantitative evidence carries the greater weight in answering the research questions, while qualitative data provide interpretive depth for puzzling or unexpected statistical findings.	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.