Comparer des méthodes

	Méta-inférence mixte à dominante quantitative	Schéma de méthodes mixtes explicatives séquentielles
Domaine	Conception de la recherche	Conception de la recherche
Famille	Process / pipeline	Process / pipeline
Année d'origine	2003–2007	2007 (formalized in Creswell & Plano Clark's mixed methods typology)
Auteur d'origine	Tashakkori & Teddlie (meta-inference concept); Creswell & Plano Clark (dominance weighting framework)	John W. Creswell & Vicki L. Plano Clark
Type	Mixed methods integration procedure	Mixed methods research design
Source fondatrice	Tashakkori, A., & Teddlie, C. (Eds.). (2003). Handbook of Mixed Methods in Social and Behavioral Research. Sage. ISBN: 978-0761920731	Creswell, J. W., & Plano Clark, V. L. (2018). Designing and Conducting Mixed Methods Research (3rd ed.). Sage. ISBN: 978-1483344379
Alias	QUAN-dominant meta-inference, quantitatively weighted meta-inference, QUAN-priority integration inference, quantitative-weighted mixed inference	explanatory sequential design, QUAN → qual design, two-phase explanatory design, sequential explanatory design
Apparentées	6	6
Résumé	Quantitative-dominant mixed methods meta-inference is an integration procedure in which the researcher draws an overarching conclusion by combining inferences from both quantitative and qualitative strands, while explicitly assigning greater evidential weight to the quantitative results. The qualitative strand serves a supporting, elaborating, or contextualizing role rather than an equal voice in the final interpretation.	The explanatory sequential mixed methods design is a two-phase research approach in which a quantitative study is conducted first, and qualitative data are then collected specifically to help explain or elaborate the initial quantitative results. The quantitative phase carries greater priority; the qualitative phase is purposefully built around the findings — such as surprising results, outliers, or statistically significant relationships — that need deeper interpretation.