Comparar métodos

	Design Quantitativo-Prioritário Participativo Misto	Meta-inferência Participativa de Métodos Mistos
Área	Delineamento de pesquisa	Delineamento de pesquisa
Família	Process / pipeline	Process / pipeline
Ano de origem	2000s–2010s	1998–2010
Autor original	Creswell & Plano Clark (core typology); Mertens (participatory-transformative lens)	Abbas Tashakkori & Charles Teddlie (meta-inference concept); extended to participatory contexts by Sweetman, Badiee & Creswell
Tipo	Mixed methods research design	Integrative inference procedure within participatory mixed methods
Fonte seminal	Creswell, J. W., & Plano Clark, V. L. (2018). Designing and Conducting Mixed Methods Research (3rd ed.). SAGE Publications. ISBN: 978-1483358468	Tashakkori, A., & Teddlie, C. (Eds.). (2010). SAGE Handbook of Mixed Methods in Social and Behavioral Research (2nd ed.). SAGE Publications. ISBN: 978-1412972666
Outros nomes	QUAN-priority participatory mixed methods, community-based quantitative-priority mixed design, participatory QUAN-dominant mixed methods, PAR quantitative-priority mixed design	PMMMI, participatory meta-inference, community-based mixed methods inference, integrated meta-inference in participatory research
Relacionados	5	1
Resumo	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.	Participatory mixed methods meta-inference is the process by which researchers and community co-investigators draw a unified, integrated conclusion — the meta-inference — from separately analysed qualitative and quantitative strands within a participatory mixed methods study. Grounded in the meta-inference framework of Tashakkori and Teddlie and extended into participatory and transformative research contexts, it treats the final synthesis of evidence not merely as a methodological step but as a collaborative, community-accountable act of knowledge production.