Mixed Methods Research : Section (A) _Group 6_Gautam Gogada_Roll no (13PGP018)


Keep Calm and Use Mixed Methods Research


As a future marketing manager set upon conquering the corporate world, I am faced with a simple question. Which is the correct method of research for my product? Should I go for qualitative research or will quantitative research give me better insights? In the quest for an answer, I suddenly had a brainwave (or at least I thought I had, for almost a minute), why not use them both? I immediately turned to my uncle ‘Google’ for help and was surprised (and a little bit disappointed, or a lot), it’s already in use. But, lucky for me, in marketing, mixed methods research has received little coverage. So, I’ll give you an introduction and few leads, which if you follow will give you an insight so that you could get a little guidance in identifying design types appropriate for various rationales or research objectives and models of different design types that have been published in marketing journals.


First things first, you will also be hearing (or seeing) something called ‘Multi method’. But let’s not get confused, in the Handbook of Mixed Methods Research, distinctions have been made between these two terms:

(1)  Multi-method which involve multiple types of qualitative inquiry (e.g. case study and ethnography) or multiple types of quantitative inquiry (surveys and experiments); and

(2) Mixed methods which involve the mixing of the two types of data (Morse,    2003).

Mixed methods research is the type of research in which a researcher or team of researchers combines elements of qualitative and quantitative research approaches (e.g. use of qualitative and quantitative viewpoints, data collection, analysis, inference techniques) for the broad purpose of breadth and depth of understanding and corroboration (Johnson et al., 2007, p. 123).


Bookish things aside (they are boring as such), let’s have a look at what mixed method research has got to offer us.

A non-judgmental comparison of qualitative and quantitative research methods

Let’s have a look at the following statements:

Pro-quantitative method student researcher: I don’t want to conduct qualitative research, I’m not convinced that it is science and besides, it’s a lot of work.

Pro-qualitative method student researcher: I don’t want to conduct quantitative research, I’ve always been bad at maths and I don’t like statistics, and besides, I am not convinced that quantitative research is an exhaustive approach.

Do they sound familiar?

Let’s face it – it is natural for a young person to be protective of what they know and what they feel comfortable with, but can you really assign the terms ‘good’ or ‘bad’ to research methods?

Ponterotto and Grieger (1999) provided us with a non-judgmental comparison of qualitative and quantitative research. According to them, employing a qualitative approach to a research issue involves looking at it from a human science perspective in which the researcher aims to describe and understand meaning derived from the data in order to generate a theory from their analysis. On the other hand, employing a quantitative approach involves looking at the issue from a natural science perspective, focusing on the quantification of observed laws and causes when testing a theory or hypothesis. Considering this, one can conclude that both quantitative and qualitative research approaches are very different. Thus, there is no straightforward way of comparing them. In fact, both approaches are highly valued by researchers from various fields and that many of them suggest a mixed methods approach involving both qualitative and quantitative measures, whenever feasible, as a valuable option (Hanson, Creswell, Clark, Petska, & Creswell, 2005).

Conquering insecurities – no room for excuses!

Now let’s have a look at the some of the common complaints about the choice of a research method, and what I have come to understand through my research experience.

“Qualitative research is not science”

According to Morgan (1998), “a science must use procedures for gathering data that are reliable across observers; and when scientists have disagreements they must know, at least in principle, how to decide the issue by data.” Therefore, in my opinion, qualitative research can be very scientific by, for example, involving independent raters to back up one’s analysis. In addition, qualitative researchers may administer standardised tests to their participants in order to enrich their analysis. To illustrate, when interviewing individuals about their experiences in relation to stress (which seems to be a common focus of many qualitative student projects), a researcher can choose to take a stress measure and to separate their participants into two groups, making it possible to compare their scores using a simple independent samples t-test.

“Qualitative research is a lot of work”

Of course it is! All researches involve hard and diligent working. I admit that I was intimidated by the lengthy transcription process of interview materials when I conducted my undergraduate research (Ouzia, 2011). This is why I chose to have my participants answer questions in writing when I conducted my research. In this way, I was able to include a qualitative component into my research while avoiding from running out of time because of transcription commitments.

It is undeniable that both statistical and qualitative data analyses can take a long time. Furthermore, student research projects are assignments with a strict deadline. Thus, choosing two very different methods for the purpose of answering one question can be a scary endeavour that is reliant on the researcher’s awareness of her own limits. Nonetheless, by taking up the challenge of research rigour and time limitation, mixed method can teach us to think more creatively, so that we can come up with a more temporally feasible approach to our research, while at the same time, produces rich and well-rounded research findings.

“Quantitative research involves math, and I don’t like math”

In my opinion and experience, statistics is a theoretical phenomenon in its own right. Statistics drive our thought process when we are drawing up a research design, for example, the question of how international university students’ anxiety affects their concentration calls for a correlation analysis. What comes after the analysis is crucial in my opinion – the discussion. Correlation analysis is the researcher’s statistical tool of choice to help her make sense of what is going on in her data, but she still has to understand why that has happened. After all, the discussion section is where all the aspects of a research project (theoretical background, methodology, results, interpretation and future direction) come together. Here, it is important to note that a qualitative research aspect can help – rather than making assumptions about the underlying reasons of a finding (i.e. anxiety correlates with concentration and is mediated by student status/ being and international student), it would enrich the analysis greatly to evaluate how participants view the effect of their fears on their concentration.

“Quantitative research is not an exhaustive approach”

I’ve saved the best for last!

I have to admit that I agree with this notion but I also want to argue that this applies to both quantitative AND qualitative research. While quantitative research often does not tap into the experiences of the participant that are relevant to what is being tested, qualitative research often fails to deliver results that are generalisable to a wider population. I think I have argued that this is the key to a mixed methods approach in depth so far – so what do you think?

In my personal experience, employing a mixed methods approach has paid off for me; while my quantitative analysis did not reveal any significant results, my qualitative analysis revealed interesting aspects regarding how siblings of autistic children’s experiences differ from siblings of typically developing children (Ouzia, 2011).

Thematic analysis – quantifying qualitative analysis

Most psychology students will come into contact with some form of education on qualitative and quantitative research methods throughout their degree. One of the qualitative analysis techniques that were addressed in my undergraduate degree was thematic analysis. This type of analysis involves the evaluation of reoccurring themes from the source of interest (i.e. interview transcript, diary, or questionnaire). A much related analysis method is content analysis, where themes or categories are predefined and looked for in the data (Subvista, 2010). The beauty of the types of analyses is that they can deliver the best of both worlds – an opportunity to evaluate personal experience and to quantify it. Not only can a researcher show that certain themes occur, but they can count them, correlate them and compare them. This is related to what I was saying earlier; statistics is a tool that can be used in many creative ways and the way I see it is as long as you know what you want to get out of your analysis, you will find a way to conduct it.

A final note – what I am NOT saying

Mixed methods approaches come in a variety of forms and provide countless exciting possibilities. I have to admit that my current research endeavours do not include qualitative research methods because of the nature of my area. A mixed methods approach is by far not the answer to all questions. Sometimes, involving a qualitative or a quantitative component in your research will not be feasible.


Refer these links for awesome articles on mixed methods research





Hanson, W. E., Creswell, J. W., Clark, V. L. P., Petska, K. S., & Creswell, J. D. (2005). Mixed methods research designs in counselling psychology. Journal of Counselling Psychology, 52, 224-235. doi: 10.1037/0022-0167.52.2.224.

Morgan, M. (1998). Qualitative research … Science or pseudo-science? The Psychologist, 11(10). 481-483.

Ouzia, J. (2011). Siblings of children with autistic spectrum disorders: experiences of stress, day-to-day life, sibling relationship and family life. (Unpublished Bachelors Dissertation). Anglia Ruskin University.

Ponterotto, J. G., & Grieger, I. (1999). Merging qualitative and quantitative perspectives in a research identity. In M. Kopala & L. Suzuki (Eds.), Using qualitative methods in psychology (pp. 49-62). Thousand Oaks, CA: Sage.

Subvista (2010, March 25). The process of thematic analysis. Retrieved fromhttp://subvista.wordpress.com/2010/03/25/new/


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