Sammenlign metoder

	Deltagende kvantitativ-prioriteret mixed design	Konkurrent triangulering mixed methods design
Fagområde	Forskningsdesign	Forskningsdesign
Familie	Process / pipeline	Process / pipeline
Oprindelsesår	2000s–2010s	2007 (formally named in Creswell & Plano Clark, 1st ed.)
Ophavsperson	Creswell & Plano Clark (core typology); Mertens (participatory-transformative lens)	John W. Creswell & Vicki L. Plano Clark
Type	Mixed methods research design	Mixed methods research design
Oprindelig kilde	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. (2011). Designing and Conducting Mixed Methods Research (2nd ed.). Sage. ISBN: 978-1412975179
Aliasser	QUAN-priority participatory mixed methods, community-based quantitative-priority mixed design, participatory QUAN-dominant mixed methods, PAR quantitative-priority mixed design	convergent parallel design, triangulation design, QUAN+QUAL concurrent design, simultaneous triangulation
Relaterede	5	5
Resumé	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.	The concurrent triangulation mixed methods design collects quantitative and qualitative data simultaneously, analyzes each strand independently, and then merges the results to assess whether the two data sources corroborate one another. Often called the convergent parallel design, it is one of the foundational configurations in mixed methods research and is chosen specifically when the researcher wants to cross-validate or triangulate findings from two distinct methodological traditions.