পদ্ধতির তুলনা করুন

	গুণগত-প্রধান মিশ্র পদ্ধতি ম্যাট্রিক্স	গুণগত-প্রধান ব্যাখ্যামূলক অনুক্রমিক মিশ্র পদ্ধতি
ক্ষেত্র	গবেষণা নকশা	গবেষণা নকশা
পরিবার	Process / pipeline	Process / pipeline
উদ্ভবের বছর	2003–2009	2000s (formalized in Creswell & Plano Clark 2007, 2011, 2018)
প্রবর্তক	Charles Teddlie & Abbas Tashakkori (matrix framework); qualitative-dominant weighting drawn from Jennifer Greene and David Morgan	Creswell & Plano Clark (explanatory sequential base); Morse (priority notation)
ধরন	Mixed methods research design variant	Mixed methods research design
মৌলিক উৎস	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
অপর নাম	QUAL-dominant MMM, qualitative-priority mixed methods matrix, QUAL-weighted matrix design, qual-dominant typology matrix	QUAL-dominant explanatory sequential design, qual-priority explanatory sequential MMR, qualitative-weighted explanatory sequential design
সম্পর্কিত	5	6
সারসংক্ষেপ	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.	The qualitative-dominant explanatory sequential mixed methods design follows a two-phase sequential structure — quantitative data collected first, qualitative data collected second — while assigning dominant analytical weight to the qualitative strand. The quantitative phase surfaces statistical patterns that require deeper explanation; the qualitative phase, which carries greater interpretive authority in this variant, provides the rich contextual understanding that the numbers alone cannot supply.