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| Kvalitativt dominerande mixed methods-matris× | Kvalitativt dominerande explorativ sekventiell mixed methods-design× | |
|---|---|---|
| Ämnesområde | Forskningsdesign | Forskningsdesign |
| Familj | Process / pipeline | Process / pipeline |
| Ursprungsår≠ | 2003–2009 | 2003–2007 |
| Upphovsperson≠ | Charles Teddlie & Abbas Tashakkori (matrix framework); qualitative-dominant weighting drawn from Jennifer Greene and David Morgan | Creswell & Plano Clark; Morse (priority notation) |
| Typ≠ | Mixed methods research design variant | Mixed methods research design |
| Ursprungskälla≠ | 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: 978-1483344379 |
| Alias | QUAL-dominant MMM, qualitative-priority mixed methods matrix, QUAL-weighted matrix design, qual-dominant typology matrix | QUAL-dominant exploratory sequential design, qual-first exploratory mixed methods, qualitative-priority exploratory sequential MMR, QUAL → quan exploratory design |
| Närliggande≠ | 5 | 6 |
| Sammanfattning≠ | The qualitative-dominant mixed methods matrix is a design variant in which the researcher selects and positions a specific mixed methods design within a typological matrix — organized by timing (sequential vs. concurrent) and paradigm weighting — while assigning greater priority to the qualitative strand. Quantitative data play a supporting, supplementary role, and the final inferences are grounded primarily in qualitative findings. | This design begins with a substantive qualitative phase (QUAL) that drives the study, followed by a smaller quantitative phase (quan) used to test, refine, or extend qualitative findings to a broader sample. The qualitative strand holds priority in both scope and interpretation; the quantitative strand serves a confirmatory or generalisability function. It is particularly well suited when theory or instrument development must be grounded in participants' own frameworks before statistical testing. |
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