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Mješovita meta-inferencija×Eksplanatorni sekvencijalni mješoviti dizajn×
PodručjeDizajn istraživanjaDizajn istraživanja
ObiteljProcess / pipelineProcess / pipeline
Godina nastanka1998–20032007 (formalized in Creswell & Plano Clark's mixed methods typology)
TvoracAbbas Tashakkori & Charles TeddlieJohn W. Creswell & Vicki L. Plano Clark
VrstaMixed methods integration procedureMixed methods research design
Temeljni izvorTeddlie, C., & Tashakkori, A. (2009). Foundations of Mixed Methods Research: Integrating Quantitative and Qualitative Approaches in the Social and Behavioral Sciences. Sage. ISBN: 978-0761930129Creswell, J. W., & Plano Clark, V. L. (2018). Designing and Conducting Mixed Methods Research (3rd ed.). Sage. ISBN: 978-1483344379
Drugi nazivimeta-inference, mixed methods overall inference, integrated inference, MMR meta-inferenceexplanatory sequential design, QUAN → qual design, two-phase explanatory design, sequential explanatory design
Srodne66
SažetakMixed methods meta-inference is the overarching conclusion drawn at the end of a mixed methods study by systematically combining and integrating the separate inferences produced by the quantitative and qualitative strands. It represents the highest-level interpretive act in mixed methods research: moving beyond strand-specific findings to produce a unified, coherent understanding of the research problem that neither strand could yield alone.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.
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ScholarGateUsporedite metode: Mixed Methods Meta-Inference · Explanatory Sequential Mixed Methods Design. Preuzeto 2026-06-17 s https://scholargate.app/hr/compare