Compara mètodes

	Disseny transformador de mètodes mixts amb pes igual	Meta-inferència participativa de mètodes mixts
Camp	Disseny de recerca	Disseny de recerca
Família	Process / pipeline	Process / pipeline
Any d'origen	2003–2011	1998–2010
Autor original	Donna M. Mertens; John W. Creswell & Vicki L. Plano Clark	Abbas Tashakkori & Charles Teddlie (meta-inference concept); extended to participatory contexts by Sweetman, Badiee & Creswell
Tipus	Mixed methods research design	Integrative inference procedure within participatory mixed methods
Font seminal	Creswell, J. W., & Plano Clark, V. L. (2018). Designing and Conducting Mixed Methods Research (3rd ed.). Sage. ISBN: 978-1483344379	Tashakkori, A., & Teddlie, C. (Eds.). (2010). SAGE Handbook of Mixed Methods in Social and Behavioral Research (2nd ed.). SAGE Publications. ISBN: 978-1412972666
Àlies	QUAN+QUAL transformative design, equal-priority transformative MMR, transformative equal-status mixed design, balanced transformative mixed methods	PMMMI, participatory meta-inference, community-based mixed methods inference, integrated meta-inference in participatory research
Relacionats	6	1
Resum	The equal-weight transformative mixed methods design combines quantitative and qualitative strands at equal priority (QUAN + QUAL) within an overarching transformative theoretical framework — such as feminist, critical race, disability rights, or social justice theory. Both data types carry equivalent evidential weight, and the entire study is structured to challenge inequity, give voice to marginalized groups, and generate findings oriented toward advocacy and social change.	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.