I am not entirely sure what you mean, but one possible mixed method design is to use quantitative sources to help you locate a purposive qualitative sample, as in quan --> QUAL. For example, you might want to compare the thoughts and experiences of groups that were either high or low on some measure.

One source to examine is Teddlie & Yu (2007) on mixed methods sampling.

Absolutely. If you, for instance, have adopted an explanatory sequential design (quant –> qual), you might have run into some unexpected or surprising quantitative findings that you would like to understand further by asking questions to people who are represented in your quantitative sample when you are doing your next qualitative phase. You might simply want to examine participants' experiences and shared (or non-shared) understandings of the phenomena that you have studied in the quantitative phase to get a kind of 'inside perspective(s)' on the associations (or lack of associations) between the variables that were found in your statistical analyses of your quantitative data. Or you may follow up your quantitative phase and findings by conducting an ethnographic or qualitative case study to examine participants-in-their-context to develop an understanding of how the variables and their possible associations might work in participants' everyday life. In these ways, the quantitative findings can guide you in terms of sampling procedure, research questions, and data collection of your next qualitative phase.

It can but it must specifically say so in chapter 5 as a recommendation.

David L Morgan Robert Thornberg La Verne A Davis Thank you so much for your answers and recommendations.

YW and best wishes!

Robert Thornberg That's just what I exactly needed to know. Many thanks indeed.

David L Morgan I've just downloaded the article you suggested. The discussion presented is very useful. Many thanks indeed.

Interesting topic. Follow.

My pleasure, Munirah Algharib ! Good luck with your work, and best wishes!

Yes, of course, if you are using explanatory design of mixed methods, it starts with a quantitative research followed by qualitative that builds on the results you got from the qualitative study. You can refer to these absolutely useful sources to support your argument:

Teddlie, C. and Tashakkori, A. (2009) Foundations of Mixed Methods Research. London: Sage.

Creswell, J. (2009) Research Design: Qualitative, Quantitative, and Mixed Methods Approaches. 3rd edn. London: Sage Publications.

Creswell, J. (2014) A concise introduction to mixed methods research. Thousand Oaks: Sage publications.

Creswell, J. and Plano Clark, L. (2011) Designing and Conducting Mixed Methods Research. London: Sage Publications.

All the literature I have ever read in mixed methods research treats a sequential explanatory design as beginning with a dominant quantitative components, as in QUAN --> qual. The point of this design is to rely on the additional strengths of qualitative methods in explaining how and why the quantitative results occur.

In contrast, quan --> QUAL is a relatively unusual design, at least in the sense that it is not widely recognized and does not have a specific label or name.

Most certainly quantitative data can be used to inform qualitative questions which then add context and clarity to a research question. The overall epistemology and methodology must be very clear and consistent to ensure the data remains complementary and that validity can b demonstrated.

Quantitative data could for example be collected from observation and collated in a licit scale table. This data in turn could be used to inform the question data base for phenomenological research to conclude to project.

𝙿𝚛𝚎𝚌𝚒𝚜𝚎𝚕𝚢, 𝚚𝚞𝚊𝚕𝚒𝚝𝚊𝚝𝚒𝚟𝚎 𝚜𝚊𝚖𝚙𝚕𝚒𝚗𝚐 𝚒𝚜 𝚍𝚎𝚌𝚒𝚍𝚎𝚍 𝚊𝚗𝚍 𝚍𝚒𝚛𝚎𝚌𝚝𝚎𝚍 𝚋𝚢 𝚝𝚑𝚎 𝚛𝚎𝚜𝚎𝚊𝚛𝚌𝚑 𝚚𝚞𝚎𝚜𝚝𝚒𝚘𝚗 𝚜𝚑𝚊𝚙𝚎𝚍 𝚊𝚗𝚍 𝚜𝚑𝚊𝚍𝚎𝚍 𝚠𝚒𝚝𝚑 𝚚𝚞𝚊𝚕𝚒𝚝𝚊𝚝𝚒𝚟𝚎 𝚌𝚘𝚗𝚝𝚘𝚞𝚛𝚜, 𝚊𝚗𝚍, 𝚟𝚎𝚛𝚢 𝚕𝚒𝚔𝚎𝚕𝚢 𝚗𝚘𝚝 𝚋𝚎𝚒𝚗𝚐 𝚚𝚞𝚊𝚗𝚝𝚒𝚏𝚒𝚊𝚋𝚕𝚎 𝚒𝚗 𝚗𝚊𝚝𝚞𝚛𝚎. 𝚄𝚜𝚞𝚊𝚕𝚕𝚢, 𝚠𝚎 𝚍𝚘 𝚚𝚞𝚊𝚕𝚒𝚝𝚊𝚝𝚒𝚟𝚎 𝚛𝚎𝚜𝚎𝚊𝚛𝚌𝚑 𝚒𝚗 𝚌𝚎𝚛𝚝𝚊𝚒𝚗 𝚜𝚌𝚎𝚗𝚊𝚛𝚒𝚘𝚜 𝚝𝚘 𝚍𝚎𝚝𝚎𝚛𝚖𝚒𝚗𝚎 𝚘𝚞𝚛 𝚚𝚞𝚊𝚗𝚝𝚒𝚝𝚊𝚝𝚒𝚟𝚎 𝚟𝚊𝚛𝚒𝚊𝚋𝚕𝚎𝚜 𝚘𝚗 𝚠𝚑𝚒𝚌𝚑 𝚏𝚞𝚛𝚝𝚑𝚎𝚛 𝚚𝚞𝚊𝚗𝚝𝚒𝚝𝚊𝚝𝚒𝚟𝚎 𝚛𝚎𝚜𝚎𝚊𝚛𝚌𝚑 𝚒𝚜 𝚞𝚗𝚍𝚎𝚛𝚝𝚊𝚔𝚎𝚗 𝚝𝚘 𝚐𝚎𝚝 𝚍𝚎𝚜𝚒𝚛𝚎𝚍 𝚛𝚎𝚜𝚎𝚊𝚛𝚌𝚑 𝚘𝚋𝚓𝚎𝚌𝚝𝚒𝚟𝚎𝚜.𝙼𝚘𝚛𝚎𝚘𝚟𝚎𝚛, 𝚚𝚞𝚊𝚕𝚒𝚝𝚊𝚝𝚒𝚟𝚎 𝚜𝚊𝚖𝚙𝚕𝚒𝚗𝚐 𝚒𝚜 𝚍𝚒𝚏𝚏𝚎𝚛𝚎𝚗𝚝 𝚋𝚊𝚕𝚕 𝚐𝚊𝚖𝚎, 𝚞𝚜𝚞𝚊𝚕𝚕𝚢 𝚙𝚞𝚛𝚙𝚘𝚜𝚒𝚟𝚎 𝚜𝚊𝚖𝚙𝚕𝚒𝚗𝚐 𝚘𝚛 𝚜𝚗𝚘𝚠𝚋𝚊𝚕𝚕𝚒𝚗𝚐 𝚏𝚞𝚕𝚕 𝚏𝚒𝚕𝚕𝚜 𝚝𝚑𝚎 𝚗𝚎𝚎𝚍, 𝚊𝚐𝚊𝚒𝚗, 𝚚𝚞𝚊𝚗𝚝𝚒𝚝𝚊𝚝𝚒𝚟𝚎 𝚛𝚎𝚜𝚎𝚊𝚛𝚌𝚑 𝚘𝚞𝚝𝚌𝚘𝚖𝚎 𝚍𝚘𝚎𝚜𝚗'𝚝 𝚜𝚑𝚊𝚙𝚎 𝚘𝚞𝚛 𝚚𝚞𝚊𝚕𝚒𝚝𝚊𝚝𝚒𝚟𝚎 𝚛𝚎𝚜𝚎𝚊𝚛𝚌𝚑.

Research questions can be derived from quantitative data, which can be further develop ed upon with more focus and in-depth analysis for qualitative data collection

Khalid Bashir I see no problem in using preliminary quantitative data to assist with qualitative sampling, as in quan --> QUAL. In particular, there are cases in which one's purposive sampling strategy requires a special set of well-defined participants that could be effectively located through a quantitative database.

Beyond that, I would not deny that research questions can be developed through preliminary quantitative data, but this a rare design compared to conducting exploratory qualitative research. In particular, many quantitative researchers discourage what they call an atheoretical "fishing expedition," so there is relatively little guidance about how to do the kind of preliminary, exploratory quantitative research that would support a quan --> QUAL design for this purpose.

Yes. This approach is very useful in mixed methods research strategy, as Morgan explained, and also to answer the original question holistically. Depends on the derived research question; but purposive sampling, with maximum variation within study population (as much as possible) can be useful.

One way to deal with the epistemological issues when working with mixed methods (there are of course several options here) is to dig into pragmatism. If you haven't read it, I would recommend David Morgan's article as an excellent start: Article Paradigms Lost and Pragmatism Regained: Methodological Impli...

Thank you everyone for the answers! I appreciate it :)))

𝙸𝚝'𝚜 𝚗𝚘𝚝 𝚚𝚞𝚊𝚗𝚝𝚒𝚝𝚊𝚝𝚒𝚟𝚎 𝚍𝚊𝚝𝚊 𝚠𝚑𝚒𝚌𝚑 𝚠𝚒𝚕𝚕 𝚊𝚜𝚜𝚒𝚜𝚝 𝚒𝚗 𝚚𝚞𝚊𝚕𝚒𝚝𝚊𝚝𝚒𝚟𝚎 𝚜𝚊𝚖𝚙𝚕𝚒𝚗𝚐, 𝚙𝚛𝚎𝚏𝚎𝚛𝚊𝚋𝚕𝚢, 𝚒𝚝'𝚜 𝚋𝚎𝚝𝚝𝚎𝚛 𝚝𝚘 𝚜𝚊𝚢 that sampling is designed purely for qualitative study with qualitative sampling techniques. Furthermore, it's c𝚎𝚛𝚝𝚊𝚒𝚗 that 𝚚𝚞𝚊𝚕𝚒𝚝𝚊𝚝𝚒𝚟𝚎 𝚊𝚛𝚎𝚊 𝚘𝚏 𝚛𝚎𝚜𝚎𝚊𝚛𝚌𝚑 can 𝚎𝚟𝚊𝚙𝚘𝚛𝚊𝚝𝚎 𝚋𝚢 𝚍𝚘𝚒𝚗𝚐 𝚚𝚞𝚊𝚗𝚝𝚒𝚝𝚊𝚝𝚒𝚟𝚎 𝚜𝚝𝚞𝚍𝚢 at times. The generated 𝚚𝚞𝚊𝚕𝚒𝚝𝚊𝚝𝚒𝚟𝚎 𝚛𝚎𝚜𝚎𝚊𝚛𝚌𝚑 𝚊𝚛𝚎𝚊 𝚘𝚞𝚝 𝚘𝚏 𝚒𝚗𝚒𝚝𝚒𝚊𝚕 𝚚𝚞𝚊𝚗𝚝𝚒𝚝𝚊𝚝𝚒𝚟𝚎 𝚛𝚎𝚜𝚎𝚊𝚛𝚌𝚑 will 𝚗𝚎𝚎𝚍 𝚎𝚡𝚙𝚕𝚘𝚛𝚊𝚝𝚒𝚘𝚗, 𝚏𝚘𝚛 𝚝𝚑𝚊𝚝 𝚠𝚎 𝚍𝚘 𝚊 𝚚𝚞𝚊𝚕𝚒𝚝𝚊𝚝𝚒𝚟𝚎 𝚜𝚝𝚞𝚍𝚢 𝚊𝚗𝚍 𝚜𝚊𝚖𝚙𝚕𝚒𝚗𝚐 𝚝𝚎𝚌𝚑𝚗𝚒𝚚𝚞𝚎 𝚒𝚜 again completely of 𝚚𝚞𝚊𝚕𝚒𝚝𝚊𝚝𝚒𝚟𝚎 𝚗𝚊𝚝𝚞𝚛𝚎, 𝚠𝚑𝚒𝚌𝚑 𝚌𝚊𝚗 𝚋𝚎 𝚏𝚊𝚜𝚑𝚒𝚘𝚗𝚎𝚍 𝚒𝚗 𝚜𝚢𝚗𝚌𝚑𝚛𝚘𝚗𝚒𝚝𝚢 𝚘𝚏 𝚢𝚘𝚞𝚛 𝚚𝚞𝚊𝚕𝚒𝚝𝚊𝚝𝚒𝚟𝚎 𝚛𝚎𝚜𝚎𝚊𝚛𝚌𝚑 𝚚𝚞𝚎𝚜𝚝𝚒𝚘𝚗. However, 𝙸 𝚊𝚐𝚛𝚎𝚎 𝚠𝚒𝚝𝚑 𝙳𝚊𝚟𝚒𝚍 𝙻 𝙼𝚘𝚛𝚐𝚊𝚗 𝚘𝚗"𝚏𝚒𝚜𝚑𝚒𝚗𝚐 𝚎𝚡𝚙𝚎𝚍𝚒𝚝𝚒𝚘𝚗 " & 𝚑𝚘𝚠 𝚝𝚘 𝚍𝚘 𝚚𝚞𝚊𝚗𝚝𝚒𝚝𝚊𝚝𝚒𝚟𝚎 𝚎𝚡𝚙𝚕𝚘𝚛𝚊𝚝𝚒ion?????

David L Morgan I'm intending to start with QUAN, and I will justify that because need to qualify my quants and consolidate them by finding supports from quotes of participants to better understand why and why not certain phenomenon has existed ... Do you think this could be doable? I know I can not guarantee findings in an early stage of my research, but I need to make sure that the data from both designs will hopefully be complementary and that validity can be established.

Munirah Algharib What is known as an "explanatory sequential design" is one of the most common approaches to mixed methods research, QUAN --> qual. In this case, the goal of the supplementary qualitative follow-up is to "better understand" how and why the quantitative results occurred.

When a phenomenon is complex with a lot of parameters and requires deep understanding, then only qualitative methods will help.

Not only can it be done it should be done. Simply structuring and running quantitative analysis is likely to generate a host of avenues for further research and as you are sitting there with data in your hands it would be wasteful not to use it in some further way. I also like to de-evolve the process a bit and think about what it is I am doing in the most basic terms. Qualitative research is born of some quantitative data in many cases. There was likely something that had some sense of numbers attached to it that initiated your desire to get into a qualitative research project I am sure. Kneed the data like dough and see what shape the cooking takes as it is in the oven.

You can definitely do a combination methods to over each limitations! However, based on your question, the only issue that I noticed is that your results cannot be generalized due to your sampling!

Thanks all for your answers!! :)

This is what is called mixed designs. Ideal way is there should be convergence. The quantitative data results should be comparable with qualitative analysed results.

In most of cases quantitative findings give you facts represented by numbers , but they may not explain why this happens - then the qualititive data will provide you the context and reasons behind the facts. Mixed method ( Quant & Qual) is for valuable interest ! I think you may go back to the same respondent to probe quantitative findings with qualitative questions.

https://www.google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=&cad=rja&uact=8&ved=2ahUKEwjb9tCFyO3rAhUIAcAKHbqHAXkQFjALegQIBBAB&url=https%3A%2F%2Fonlinelibrary.wiley.com%2Fdoi%2Fpdf%2F10.1002%2F1098-240X%2528200006%252923%253A3%253C246%253A%253AAID-NUR9%253E3.0.CO%253B2-H&usg=AOvVaw3AVkQ7Td8EAjkudbvinb6L

Adeyemi Oluwole Thank you!

You may read the book from John W Creswell "Research Design Qualitative, Quantitative, and Mixed Methods Approaches": very useful for your answer.

Thank You!