Salīdzināt metodes

	Kvantitatīvi dominējoša jauktu metožu meta-inferenču	Kvantitatīvi prioritārs jaukto metožu dizains
Nozare	Pētījuma dizains	Pētījuma dizains
Saime	Process / pipeline	Process / pipeline
Izcelsmes gads	2003–2007	2003–2009
Autors	Tashakkori & Teddlie (meta-inference concept); Creswell & Plano Clark (dominance weighting framework)	Creswell & Plano Clark; Teddlie & Tashakkori
Tips	Mixed methods integration procedure	Mixed methods research design
Pirmavots	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
Citi nosaukumi	QUAN-dominant meta-inference, quantitatively weighted meta-inference, QUAN-priority integration inference, quantitative-weighted mixed inference	QUAN-dominant mixed methods, quantitative-dominant mixed methods, quan-priority design, quantitative-first mixed methods
Saistītās	6	6
Kopsavilkums	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.	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.