Порівняння методів

	Вбудований змішаний дизайн із пріоритетом кількісних даних	Вбудований змішаний дизайн з якісним пріоритетом
Галузь	Дизайн дослідження	Дизайн дослідження
Родина	Process / pipeline	Process / pipeline
Рік появи	2003–2011	2007 (first edition of Designing and Conducting Mixed Methods Research)
Автор методу	Creswell & Plano Clark (embedded structure); Morse & Niehaus (priority notation)	Creswell & Plano Clark
Тип	Mixed methods research design	Mixed methods research design
Основоположне джерело	Creswell, J. W., & Plano Clark, V. L. (2011). Designing and Conducting Mixed Methods Research (2nd ed.). Sage. ISBN: 978-1412975179	Creswell, J. W., & Plano Clark, V. L. (2018). Designing and Conducting Mixed Methods Research (3rd ed.). Sage Publications. ISBN: 978-1483358468
Інші назви	QUAN+qual embedded design, quantitative-dominant embedded mixed methods, embedded QUAN design, embedded quantitative-priority design	qual-dominant embedded design, qualitative-primary embedded MMR, embedded QUAL+quan design, nested qualitative-priority design
Пов'язані	5	5
Підсумок	The embedded quantitative-priority mixed design is a mixed methods research structure in which a dominant quantitative study (survey, experiment, or longitudinal assessment) provides the primary basis for conclusions, while a qualitative component is embedded within that quantitative framework to address a question the numbers alone cannot answer. Priority and resources lie with the quantitative strand; the qualitative strand enriches, contextualizes, or explains a specific aspect of the larger quantitative investigation.	The embedded qualitative-priority mixed design nests a secondary quantitative strand within a dominant qualitative inquiry. The qualitative strand drives the research logic, framing the questions, guiding data collection, and anchoring interpretation, while the quantitative component plays a supporting role — typically measuring outcomes, tracking context variables, or confirming patterns emerging from the qualitative core. The result is a rich, theoretically grounded account that remains rooted in participants' meanings while gaining empirical precision where needed.