The aim of mixed methods research is to answer the research question by blending quantitative and qualitative research parts. Since mixed methods research aims to exhibit the advantages of both qualitative and quantitative research, a fuller picture can be obtained by using mixed techniques than a single quantitative or qualitative study.
In the social, medical, and behavioural sciences, mixed methods research is frequently employed, especially in interdisciplinary subjects and societal studies.
Examples of mixed methods research
When should you conduct mixed methods research?
If quantitative or qualitative data alone can’t address the research questions in your research design, mixed methods research may be the best solution. Mixed methods research is often employed for several reasons, including:
Qualitative research cannot be generalised due to the smaller sample size. However, the comparative weakness in the mixed methods research can be eradicated by comparing the strength of ‘large N’.
Using different approaches helps to contextualise your results and give additional context to your findings. For example, using qualitative data to support quantitative results can help your research become “active.”
If you are looking to increase the credibility of your findings, you will need to employ several different data collection techniques. First, the credibility of your findings is enhanced if the qualitative and quantitative data concur. It is called triangulation.
You will need to discuss how the qualitative and quantitative methodologies would be integrated into your research when constructing your research topic. For example, if a single quantitative or qualitative study can adequately address your research topic, a mixed techniques approach may not be the best choice.
Example of research
You wish to investigate bicycle safety in Rotterdam’s high-traffic zones. It might be a simple quantitative study if you’re curious about accident frequency and location. On the other hand, a qualitative approach may be appropriate if you’re concerned with the type of complaints from cyclists or their impressions of cycling in certain city areas.
However, if you truly want to combine both issues in one research study, mixed methods research can be a viable option.
For instance, you might utilise mixed methods research to investigate if areas deemed risky have a high accident rate or to understand why particular locations are more hazardous for cycling than others.
Remember that mixed methods research is much more than collecting qualitative and quantitative data; you must also evaluate the link between the two, figure out how to combine them and come up with a logical conclusion. Mixed methods research is a less common choice for researchers since it is much more complicated to execute than simple qualitative or qualitative research.
Mixed-methods research designs
Mixed methods research methodologies come in several different forms. The contrasts between them are based on the research’s goal, the time of collection of the data, and the credence assigned to each type of data.
Here are the most important things to remember when conducting mixed methods research:
Here are some of the most typical types of mixed techniques designs.
In the case of a convergent parallel method, both quantitative and qualitative data are collected simultaneously but are then assessed separately. Once finished, the data is compared to draw broad conclusions.
Example of convergent parallel design
You do both aspects of your research concurrently in your study of riding safety in Rotterdam:
After you’ve finished collecting and analysing data, you’ll compare the outcomes and connect your results.
In the case of an embedded design, the researcher gathers and analyses both data types simultaneously but within the framework of a larger quantitative or qualitative design. In this case, one data type is considered secondary to the other.
If you have a limited time or budget, this is an excellent strategy. An embedded design can be used to augment or supplement the findings of the main research design.
Embedded design example
Qualitative interviews with riders who filed complaints as part of a quantitative study can be “embedded” to test if the frequency of bike complaints about a region corresponds with the accident rates. In this case, much of the data would be quantitative.
Quantitative data gathering and evaluation come first in the case of an explanatory sequential design, followed by the collection and analysis of qualitative data.
You must implement this design if you believe that the qualitative data would define and summarise your quantitative results.
Explanatory sequential example
You start by looking at accident records and making educated guesses about which regions are the riskiest for cyclists. Then, based on your results, you undertake a qualitative analysis of complaints and interviews with bikers in high-accident regions.
You may use qualitative analysis to demonstrate why accidents happen on certain routes and further into specific issue regions.
In the case of an exploratory sequential design, the researcher prioritises qualitative data gathering and its analysis above quantitative data collection and analysis.
The approach can be used to answer fundamental problems and produce hypotheses. The quantitative data can then be selected to check or verify the qualitative findings.
Example of Exploratory sequential design
You start by interviewing riders to understand the issues and establish some early judgments. Then you look at accident statistics to see if cyclist perceptions match where accidents happen.
Mixed-methods research has several advantages.
Mixed methods research can be applied if you want to take advantage of both the contextualised insights and quantitative data. In this case, one data type’s strength often helps mitigate the weakness of the other.
For instance, if you are using only quantitative studies, it might fail to describe the experience and emotions of the participants of the study. Therefore, a qualitative approach will help to enrich and better describe your results.
Since qualitative studies are rarely generalisable, incorporating the quantitative side will help to enhance validity.
Researchers are far less constrained when using mixed methods research since it is much less inclined toward general research rules and disciplines. It helps researchers be more flexible in terms of research design, helping them integrate various aspects of other research types to conclude.
When using mixed methods, researchers combine their hypothesis and generate theory which is not the case when using simple quantitative or qualitative research.
Mixed-methods research has several drawbacks.
It takes a lot of time to conduct mixed methods research. Gathering, evaluating and combining these two types of data is labour-intensive work and demands the involvement of bigger research teams. It makes mixed methods research quite expensive.
In case of contradictory outcomes from mixed methods research, one can generate contradicting results, which can be quite difficult to interpret. If both data types do not match or if confounding variables are present, it can make the results much more confusing
Since both quantitative and qualitative data have two quite distinct forms, it may be difficult to develop techniques for comparing outcomes in a systematic manner
Ans. Researchers often combine data types from both quantitative and qualitative studies to answer the research question in the case of mixed methods research.
Ans. The systematic method of gathering data or observations in research is data collecting.
Ans. In the case of quantitative research typically deals with stats and numbers, whereas words and concepts are generally dealt with by qualitative research.
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