Порівняння методів

	Партисипативний дизайн змішаних методів з пріоритетом кількісних даних	Кількісно-пріоритетний змішаний метод дослідження
Галузь	Дизайн дослідження	Дизайн дослідження
Родина	Process / pipeline	Process / pipeline
Рік появи	2000s–2010s	2003–2009
Автор методу	Creswell & Plano Clark (core typology); Mertens (participatory-transformative lens)	Creswell & Plano Clark; Teddlie & Tashakkori
Тип	Mixed methods research design	Mixed methods research design
Основоположне джерело	Creswell, J. W., & Plano Clark, V. L. (2018). Designing and Conducting Mixed Methods Research (3rd ed.). SAGE Publications. ISBN: 978-1483358468	Creswell, J. W., & Plano Clark, V. L. (2018). Designing and Conducting Mixed Methods Research (3rd ed.). Sage. ISBN: 978-1483344379
Інші назви	QUAN-priority participatory mixed methods, community-based quantitative-priority mixed design, participatory QUAN-dominant mixed methods, PAR quantitative-priority mixed design	QUAN-dominant mixed methods, quantitative-dominant mixed methods, quan-priority design, quantitative-first mixed methods
Пов'язані	5	6
Підсумок	Participatory quantitative-priority mixed design combines a community-engaged, participatory research framework with a mixed methods structure in which the quantitative strand carries primary weight. Stakeholders and community members co-shape research questions, instruments, and interpretation, while quantitative data provide the dominant evidence base and qualitative data serve a complementary, explanatory, or contextualizing role. This design is particularly suited to applied, evaluative, and social-justice-oriented inquiry where both statistical rigor and community voice are required.	Quantitative-priority mixed methods design is a research approach in which quantitative data and analysis carry the primary explanatory weight, while qualitative data play a supplementary or corroborating role. The researcher collects and analyzes quantitative data first (or concurrently with greater emphasis), then uses qualitative findings to elaborate, explain, or contextualize the statistical results. Priority and sequence together define where integration occurs and how each strand informs the other.