There are quite a number of books on "mixed methods research" that directly address the kinds of questions you are asking (two well-known ones are by Creswell & Plano-Clark, and Creamer).

One thing that mixed methods does is to consider the match between a variety of research designs and the kinds of questions that are commonly asked in the field. For example, sequential exploratory designs can be represented as qual --> QUANT, where qualitative methods are used to develop the content of largely qualitative studies. Alternatively, sequential explanatory designs (QUANT --> qual) use follow-up qualitative studies to better understand the outcomes from earlier quantitative research.

But notice that neither of those designs features a major QUAL study, where designs like that are known as "qualitatively driven" mixed methods.

Finally, the term "triangulation" is now considered out of date because it came to mean too many different things. On the one hand, it could mean "convergence" where you compare whether the two methods produce similar results. On the other hand, it could mean "complementarity" where each method adds a different strength to the overall project.

The SciCBN Contemplative Lab is all about these topics, and network-model collaborations as an online hub would be a calling as posted on researchgate.net/profile/green_moon2 and independent.academia.edu.laurencewilliamson

Comparative Analysis

Qualitative and quantitative methods are complementary and each of them has a place in research depending on the data types. The analysis goes as far as it can give appropriate answers to the set research questions.

There are quite a number of books on "mixed methods research" that directly address the kinds of questions you are asking (two well-known ones are by Creswell & Plano-Clark, and Creamer).

One thing that mixed methods does is to consider the match between a variety of research designs and the kinds of questions that are commonly asked in the field. For example, sequential exploratory designs can be represented as qual --> QUANT, where qualitative methods are used to develop the content of largely qualitative studies. Alternatively, sequential explanatory designs (QUANT --> qual) use follow-up qualitative studies to better understand the outcomes from earlier quantitative research.

But notice that neither of those designs features a major QUAL study, where designs like that are known as "qualitatively driven" mixed methods.

Finally, the term "triangulation" is now considered out of date because it came to mean too many different things. On the one hand, it could mean "convergence" where you compare whether the two methods produce similar results. On the other hand, it could mean "complementarity" where each method adds a different strength to the overall project.

Please do not look for a ‘balance’. Nearly every research starts by conceptualising a space. We imagine action in a space. Subsequently, we should draw both quantitative and qualitative tools.The dichotomy of the two arises from the researcher’s inabilities. That is why we need interdiscplinarity. We need researchers equipped with composite tools. Our complex realities demand we do so. Ponder further here:

Article Parsing Competitive Dialogue in Public-Private Partnerships:...

Article Parsing Competitive Dialogue in Public-Private Partnerships:...

I am following the answers with keen interest.David Morgan please expand what you mean by 'triangulation is out of date'.I am actually justifying triangulation in my paper positioning it as a clever thing to do? Please also indicate references to go to.Thank you in advance for your help.

The problem is, as I said, that the term triangulation no longer has a single, clear meaning. Consequently, the editors of the Journal of Mixed Methods Research have issued a statement asking that articles no longer use the term triangulation.

I have written a response to that editorial, which I have attached (note that it also contains a citation to the original editorial).

Preprint Commentary: After Triangulation, What Next?

Prof thank you very much.I concur because as I was writing the justification it was becoming very clear to me that there was confusion.Is it data collection triangulation, triangulation of the analysis or methods and how do they apply to trustworthiness? It was really becoming difficult for me to write a convincing justification with contradictory support from literature .Thank you very much for the clarification and help.

In mixed methods, the usual approach to "triangulation" is based on the comparison of the results from the separate studies.

Triangulation for trustworthiness is usually used within qualitative research, where the goal is "convergence" so that the separate qualitative results produce similar conclusions.

This triangulation function, Professor, is very much the 3Dimensional and 'dimensional branch-studies comparison' in Consciousness Studies, that in analytical research dialog is a contraposition of postulates, this also being a quantitative aspect in the Chomskian science. You expressions are guidelines of paradigmatic integration.

Triangulation originally referred to the intersection to two separate measurements at the point of a triangle. It was an analogy to methods of navigation, and there was no connection to three dimensions.

Well over forty years ago I was given a good rule of thumb (and I hope that phrase translates well for nonnative English speakers). Qualitative methods are stronger on validity, and have weaknesses in reliability. Likewise, quantitative methods are usually more reliable but may have weaknesses in validity. If you can combine qualitative and quantitative data in the same work, their respective strengths and weaknesses do complement each other.

Jacek

'in a nutshell the 'balance' of the research methods you might use will be a matter of your judgement as to how well certain methods (singularly or in combination) might help you to answer your research question.

more important is the aim of the research, not 'balance'. We use methods according to the goals ;-)

An understanding of the strengths/weaknesses/features of qualitative/quantitative approaches could help/facilitate in making a choice, please see the comparison/illustrations: Johnson and Onwuegbuzie, 2004, pp. 19-20; Anderson, 2010, pp. 2-3; Schulze, 2003, p. 12; Gelo et al, 2008, pp. 271-274; Libarkin and Kurdziel, 2002, pp. 78-79; Amaratunga et al, 2002, pp. 20-23.

• Amaratunga, D., Baldry, D., Sarshar, M. and Newton, R. (2002) Quantitative and qualitative research in the built environment: application of "mixed" research approach, Work study, 51, 1, pp. 17-31.
• Anderson, C. (2010) Presenting and Evaluating Qualitative Research, American Journal of Pharmaceutical Education, 74, 8, pp. 1-7.
• Gelo, O., Braakmann, D. and Benetka, G. (2008) Quantitative and Qualitative Research: Beyond the Debate, Integrative Psychological and Behavioral Science, 42, 3, pp. 17-31.
• Johnson, R. B. and Onwuegbuzie, A. J. (2004) Mixed Methods Research: A Research Paradigm Whose Time Has Come, Educational Researcher, 33, 7, pp. 14-26.
• Libarkin, J. C. and Kurdziel, J. P. (2002) Research Methodologies in Science Education: The Qualitative-Quantitative Debate, Journal of Geoscience Education, 50, 1, pp. 78-86.
• Schulze, S. (2003) Views on the combination of quantitative and qualitative research approaches, Progressio, 25, 2, pp. 8-20.

Thank you all for your insights. Not wanting to make this discussion longer, but running that risk I have a related question. Having read David Morgan's reply to the statement of journal JMMR I and agreeing that eliminating "triangulation" is not the solution, my question is: Should not all are 'mixed' data anlyses be clear bout it purposes follwing a clear terminology like the one proposed by Green et al (1989): Triangulation Complementarity, Dvelopment, Initiation, Expansion.

Much of the discussion of integration in MMR has revolved around research designs (either from a typology or interactive approach), with clear taxonomies developed for this specific purpose. My impression is that when it comes down to the integration of data analysis and interpreation, there is still some lack of clarity re the need to define purposes (for the integration of data) across individual studies.

References used in the post:

Greene, J. C., Caracelli, V. J., & Graham, W. F. (1989). Toward a conceptual framework for mixed-method evaluation designs Educational Evaluation and Policy Analysis, 11(3), 255-274.

Integration and how to achieve it has been an ongoing issue in mixed methods. One result has been a series of typologies for research designs, where each design supplies a clear set of purposes for its use. In the most recent edition of their textbook on mixed methods, Creswell and Plano-Clark review a large number of these typologies, but in my opinion almost all of them have their roots in the original set proposed by Greene, Caracelli, and Graham.

And as a point of clarification, I prefer to see the term triangulation replaced by a set of terms that each capture one of the multiple purposes that have been assigned to it, such as convergence when the goal is to examine whether the conclusions from different methods are similar, and complementarity when the goal of using multiple methods is to have each contribute different strengths.

Thank you very much David. I am familair with Creswell and Plano-Clark recent (2017) edition where they proposed three core designs instead of the six proposed in the 2011edition of the book. What I was trying to ask was that although a design does 'force' us to define our purposes in terms of integration in various regards, whether the ultimate gol of MMR is that integration reaches the data analysis level? Many times we see studies merely 'concatenating' separate data sets and not really 'blending' their strengths. So, when we think of integration, should n't we be thinking at diferent levels? For instance: (a) in terms of the broader research design (b) data anlysis and interpration, (c) the integration of paradigms via a 'dialectical stance' like pragmatism

I usually say that what we want to integrate are the results from the different methods, but that requires first specifying a goal or purpose for each method within the overall project. In terms of choosing a research design, I think the order of your thinking should be to specify a goal, and then choose a design that can address that goal.

For issues like choosing between pragmatism and a dialectical stance, I think both of these approaches (as well as all the other major paradigms in mixed methods) agree that the choice of methods and designs depends on the nature of the research question. Given that level of agreement, then the choice of a paradigm depends on your larger goals, such as who your audience is, or what you want to accomplish with your results (e.g., participatory action research).

And as far as Creswell and Plano-Clark's three designs ago, I think that is far too limited. In particular, they do not include any designs that are qualitatively driven. So, those may be the three most frequently used designs, but that may just reflect the continuing dominance of quantitative research in many fields.

Thank you very much David L Morgan . Your comments were very insightful, as always. Have to say I totally agree with you on the three designs prposed by Creswell and Plano Clark (2018). I do understand why they reduced the no. of designs, but find it too broad. Having adopted a multiphase mixed methods design (embedding a case study component) I find that their current typology is unable to explain my design in such a clear way.

Hi Jacek

I would like to add a related paper to your point 4. If I understood correctly you are interested when the data saturation is reached in qualitative part of your mixed-method approach. Besides, I like the book from Creswell (2014) about mixed-methods because of the good explanations of the different approaches.

Regards

Roland

Literature:

Creswell, J. W. (2014). A concise introduction to mixed methods research. Sage Publications.

Fusch, P. I., & Ness, L. R. (2015). Are we there yet? Data saturation in qualitative research. The qualitative report, 20(9), 1408-1416.

I'm not sure why Creswell and Plano-Clark reduced the number of designs that they cover in detail, especially since there has been an increasing interest in more complex designs within the field as a whole. Another interesting development has been that sequential designs with three or more elements are now often referred to as "longitudinal" designs, but I personally think that mostly reflects a lack of experience (and imagination) in considering more complex designs.

Every researcher will find its own balance and perhaps sometimes just stick to one way. However that one way is never the highway and must be complemented with the other. Use of both is better.

well, for me it depends on the objectives where you want to dress matter which method to use more and how to balance methods used in a given research. It has been discuss by different anthers like Cromwell on how to select research method used in a given studies, similarly, Zikmund ( 2003) Saunders,et.al., ( 2005) and others has clearly articulate the selection process and balancing method used by the researcher .Especially the Saunders 'Research Onion model may helps more on balancing the method use more in a given research .

As with so much in research, balance of research methods used comes down to adequately answering your research question: qual. / quant. / qual.-quant. / quant.-quant. / qual. / qual.?

would you compare the balancing topics of our Online Lab on researchgate and by inspired ideas from these, considering many topics introduced are specialist areas, and well said some. The branches of complementary is the tree Atmanspacher phrases, and those of an analytical experiential philosophy is a qualitative Unis Mundis, Donnald Hoffman has established the quantum calculus on QUANT, and that Is to the limits of a coherent foundation for philosophy of science and as recognised unified postulate that comes meditational. Thanks

Hello

I am Phd and I design a mixed procedures + contrast, so qualitative (study cases) + quantitative (descriptive) for my job was deep position. My thesis is her in RG.

BR

Ingrid

Just go through the Mixed method books.

Dr Kamath Madhusudhana