Interesting points raised by the preceding speakers.  I would take a step back and ask you the question 'What is it you are trying to understand?'  This may help with which epistemology/theoretical perspective/methodology/data collection method you choose..  Have look at M. Crotty 'The foundations of Social Research' for insight into the slippery slop of postmodernism.  Lastly, the term mixed methods is hard to define in the current state of research, it was very prevalent in the 1990's and now the decision on what is the best data collection method available to to answer my research question(s) has taken center stage.  What tends to happen frequently is multiple methods of data collection are employed to produce the best insight into what you are researching.  You my use either a positivist, ,interpretivist, critical inquiry, feminist or post modernist (to name a few)  theoretical perspective, but collect data from multiple methods.  This can give you triangulation through what is known as multimethod research.  Have a look at j Brewer 'Foundations of Multimethod Research Synthesizing Styles' as good text on this subject.  I hope this helps you? .       

I have two papers available on ResearchGate that discuss pragmatism and mixed methods. The primary advantage of pragmatism versus post-positivism would be, as others have pointed out, that the subjective approach in qualitative methods is an uncomfortable assumption for post-positivists.

Also, triangulation only requires two methods, since the analogy is to the convergence of the separate sets of results, like two lines coming together at the point of a triangle . But note that the word triangulation has been used in so many ways that most people in the field of mixed methods now prefer the term convergence for designs that directly compare the equivalence of results from qualitative and quantitative studies.

Hello chaudry

Let me clear me about triangulation first. It's combination of quali and quanti, no more which one come first. 

In your you have to do quali first and then quantitative. Lastly for triangulation, you have conclude based on results of quali and quanti

Wait a minute Ahmad,

Triangulation is not just what your report, far from it. Here is a more definitive definition of triangulation from Jick "Mixing Qualitative and Quantitative Methods: Triangulation in Action"

Triangulation is broadly defined by Denzin (1 978: 291) as "the combination of methodologies in the study of the same phenomenon." The triangulation metaphor is from navigation and military strategy that use multiple reference points to locate an object's exact position (Smith, 1 975: 273). Given basic principles of geometry, multiple viewpoints allow for greater accuracy. Similarly, organizational researchers can improve the accuracy of their judgments by collecting different kinds of data bearing on the same phenomenon. In the social sciences, the use of triangulation can be traced back to Campbell and Fiske1 (1959) who developed the idea of "multiple operationism."They argued that more than one method should be used in the validation process to ensure that the variance reflected that of the trait and not of the method. Thus, the convergence or agreement between two methods ". . . enhances our belief that the results are valid and not a methodological artifact" (Bouchard, 1976: 268). This kind of triangulation is labeled by Denzin (1 978: 302) as the "between (or across) methods" type, and represents the most popular use of triangulation. It is largely a vehicle for cross validation when two or more distinct methods are found to be congruent and yield comparable data.

For organizational researchers, this would involve the use of multiple methods to examine the same dimension of a research problem. For example, the effectiveness of a leader may be studied by interviewing the leader, observing his or her behavior, and evaluating performance records. The focus always remains that of the leader's effectiveness but the mode of data collection varies. Multiple and independent measures, if they reach the same conclusions, provide a more certain portrayal of the leadership phenomenon. Triangulation can have other meanings and uses as well. There is the "within-method" kind (Denzin, 1978: 301) which uses multiple techniques within a given method to collect and interpret data. For quantitative methods such as survey research, this can take the form of multiple scales or indices focused on the same construct. For qualitative methods such as participant observation, this can be reflected in "multiple comparison groups" (Glaser and Strauss, 1965: 7) to develop more confidence in the emergent theory. In short, "within-method" triangulation essentially involves cross-checking for internal consistency or reliability while "between-method" triangulation tests the degree of external validity

As you can see triangulation.can have broader application than what your propose.

Regards,

Keith

Please excuse me for waking this topic up but it most pertinent to my interests. Firstly, for QUAL I intend to (initially at least) code deductively using theoretically derived codes to see if theories developed looking at other areas of service provision holds within my area of interest (construction professionals). In the advanced stages of analysis I intend to code more inductively to look for something unexpected. However I am using the QUAL phase mainly to check for what I think im going to find. No doubt this is not an appropriate approach for anyone attempting to do what Braun and Clarke (2013) describe as 'Big Qual". I wouldnt even consider it if, say I was using the Charmez version of constructivist grounded theory for the QUAL phase. But I think it might be appropriate for my approach. Furthermore i'm using their version of thematic analysis which they argue is flexible and not tied to one particular paradigm. At the moment I can find more evidence against my approach than for it. As well as your comments I see Creswell & Plano-Clark in their MMR book seem to argue against it. However their description of post-positivism just looks like positivism to me and I was under the impression that post-positivism was more than just 'positivism-light' and there was genuinely room for a bit of induction and subjectivity.

I agree that Braun & Clarke accept both using pre-determined codebooks and inductively derived codebooks, and combining the two has been referred to as a hybrid approach (Fereday & Muir-Cochrane, 2006).

In what mixed methods researchers refer to as a "sequential explanatory" design (QUANT --> qual), it would certainly make sense to have a predetermined coding system based on the research questions and results from the quantitative component, which could be expanded by new observations in the qualitative data. So, from that point of view, your approach would not be problematic at all.

Beyond that, I'm not sure why you are adding post-positivism to the discussion. The core element of post-positivism is that although there is a reality external to our beliefs, we can never know it with certainty. One of the key elements of post-positivism is that we can reject results that do not match our theories about reality, but the inability to to reject a hypothesis does not imply that it is a "true" reflection of reality because that result might be due to any number of other factors. But these kinds of abstract issues seem to go well beyond the practical concerns that are central to your needs.

Thank you for your response David. My intended approach is QUAL-QUANT exploratory sequential. I was considering pragmatism but recently wondered about the potential for post-positivism as firstly it aligns with my personal beliefs and secondly I am finding pragmatism problematic, mainly because of the different variants and attempting to reconcile them as a philosophy applicable to my research aims. Another researcher using a similar design questioned the potential of critical realism on this forum to which you suggested post-positivism may be more accessible option given the late stage of his research. Please excuse any ignorance as I am a relative novice.

What kind of coding approach you use for the qualitative portion of an exploratory sequential design (qual --> QUANT) depends on how much theoretical development you already have for the quantitative portion. For example, you might have a number of predetermined concepts that you know you want to include, so the primary purpose of the qualitative study would be to help operationalize those topics.

If that is your goal, what difference would it make if you approached this task from a pragmatist, post-positivist, or critical realist stance? In each case, you would collecting and analyzing the same type of data for the same purposes, with the same outcomes regardless of your "paradigm."

Personally, this is why I prefer pragmatism -- because it focuses on what you are trying to accomplish (i.e., your beliefs and the outcomes of putting those beliefs into action). But the key question(s) that pragmatism asks are: what difference would it make to believe one thing rather another (or to act one way versus another). In this case, you are going to take a set of actions based on your data-driven needs, and it won't make any difference what you believe about the nature of reality.So, why are you letting such abstract issues get in the way of doing the research itself?

Thanks for that David. I just want to get on the right track from the beginning and ensure decisions I make are thought-through and justifiable.