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Kvantitativně-dominantní meta-inference smíšených metod×Design smíšených metod s konvergentní triangulací×
OborDesign výzkumuDesign výzkumu
RodinaProcess / pipelineProcess / pipeline
Rok vzniku2003–20072007 (formally named in Creswell & Plano Clark, 1st ed.)
TvůrceTashakkori & Teddlie (meta-inference concept); Creswell & Plano Clark (dominance weighting framework)John W. Creswell & Vicki L. Plano Clark
TypMixed methods integration procedureMixed methods research design
Původní zdrojTashakkori, A., & Teddlie, C. (Eds.). (2003). Handbook of Mixed Methods in Social and Behavioral Research. Sage. ISBN: 978-0761920731Creswell, J. W., & Plano Clark, V. L. (2011). Designing and Conducting Mixed Methods Research (2nd ed.). Sage. ISBN: 978-1412975179
Další názvyQUAN-dominant meta-inference, quantitatively weighted meta-inference, QUAN-priority integration inference, quantitative-weighted mixed inferenceconvergent parallel design, triangulation design, QUAN+QUAL concurrent design, simultaneous triangulation
Příbuzné65
ShrnutíQuantitative-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 concurrent triangulation mixed methods design collects quantitative and qualitative data simultaneously, analyzes each strand independently, and then merges the results to assess whether the two data sources corroborate one another. Often called the convergent parallel design, it is one of the foundational configurations in mixed methods research and is chosen specifically when the researcher wants to cross-validate or triangulate findings from two distinct methodological traditions.
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ScholarGatePorovnat metody: Quantitative-dominant mixed methods meta-inference · Concurrent Triangulation Mixed Methods Design. Získáno 2026-06-17 z https://scholargate.app/cs/compare