Comparer des méthodes

	Schéma de méthodes mixtes quantitatives dominantes multiniveaux	Schéma de méthodes mixtes à priorité quantitative
Domaine	Conception de la recherche	Conception de la recherche
Famille	Process / pipeline	Process / pipeline
Année d'origine	2003–2010	2003–2009
Auteur d'origine	Tashakkori & Teddlie (multilevel MMR); dominant-status typology formalized by Morse (1991) and elaborated by Tashakkori & Teddlie	Creswell & Plano Clark; Teddlie & Tashakkori
Type	Mixed methods research design	Mixed methods research design
Source fondatrice	Tashakkori, A., & Teddlie, C. (Eds.). (2010). SAGE Handbook of Mixed Methods in Social and Behavioral Research (2nd ed.). Sage Publications. ISBN: 978-1412972666	Creswell, J. W., & Plano Clark, V. L. (2018). Designing and Conducting Mixed Methods Research (3rd ed.). Sage. ISBN: 978-1483344379
Alias	QUAN-dominant multilevel MMR, multilevel mixed methods with quantitative priority, QUAN-priority multilevel design, dominant-status multilevel mixed methods	QUAN-dominant mixed methods, quantitative-dominant mixed methods, quan-priority design, quantitative-first mixed methods
Apparentées	6	6
Résumé	Quantitative-dominant multilevel mixed methods design is a mixed methods approach in which quantitative inquiry carries the primary evidential weight while qualitative data play an auxiliary, illuminating role, and both strands are applied across two or more hierarchically nested levels of analysis — for example, students within classrooms within schools. The design is suited to research questions that require both statistical modeling of nested structures and contextual understanding of how those structures operate.	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.