विधियों की तुलना करें
चुनी हुई विधियों की आमने-सामने समीक्षा करें; भिन्नता वाली पंक्तियाँ रेखांकित हैं।
| मिश्रित विधि मेटा-अनुमान× | बहु-चरण मिश्रित विधि डिज़ाइन× | |
|---|---|---|
| क्षेत्र | अनुसंधान अभिकल्प | अनुसंधान अभिकल्प |
| परिवार | Process / pipeline | Process / pipeline |
| उद्भव वर्ष≠ | 1998–2003 | 2007 (first edition of Designing and Conducting Mixed Methods Research) |
| प्रवर्तक≠ | Abbas Tashakkori & Charles Teddlie | John W. Creswell & Vicki L. Plano Clark |
| प्रकार≠ | Mixed methods integration procedure | Mixed methods research design |
| मौलिक स्रोत≠ | Teddlie, C., & Tashakkori, A. (2009). Foundations of Mixed Methods Research: Integrating Quantitative and Qualitative Approaches in the Social and Behavioral Sciences. Sage. ISBN: 978-0761930129 | Creswell, J. W., & Plano Clark, V. L. (2018). Designing and Conducting Mixed Methods Research (3rd ed.). Sage. ISBN: 978-1483substitute |
| उपनाम | meta-inference, mixed methods overall inference, integrated inference, MMR meta-inference | multiphase design, multiproject mixed methods, programmatic mixed methods, multistage mixed methods |
| संबंधित | 6 | 6 |
| सारांश≠ | Mixed 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 multiphase mixed methods design is a sustained research program in which quantitative and qualitative strands are combined across three or more sequential phases — or across multiple related projects — to address a central program objective. Each phase builds on the prior phase's findings, making the design well-suited to long-term evaluation, intervention development, and large-scale program assessment where a single data-collection cycle cannot fully address the complexity of the research problem. |
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