Mixed Methods Research | Types & Examples
Mixed methods research combines qualitative methods, which use nonnumerical data like text, transcripts, and images, with quantitative methods, which use numerical data.
A common misconception is that mixed methods studies simply include both qualitative and quantitative data. However, when adopting a mixed methods approach, you must carefully consider when and how to collect and integrate these different data sources. Mixed methods research can therefore be time consuming, but it offers the benefit of providing a more holistic answer to your research question.
What is mixed methods research?
As its name suggests, mixed methods research uses a blend of research methods. By combining quantitative and qualitative approaches, mixed methods research can provide deep insight into nuanced research questions.
Quantitative research uses numerical data to identify patterns, compare groups, and identify cause-and-effect relationships. Researchers using quantitative methods assume there is one “absolute truth” that can be uncovered through unbiased statistical analysis (this perspective is called positivism).
Qualitative research instead uses narrative data, including text, pictures, and audio and video recordings, to understand people’s behavior and beliefs. Qualitative research leaves space for different perspectives and opinions related to a phenomenon (this perspective is called interpretivism).
To study this topic using quantitative methods, you might distribute a survey where students rank how much pressure they feel to succeed academically due to factors like familial pressure, career prospects, and scholarship requirements. You could also have them complete standardized anxiety and depression scales and look for correlations between the survey data and mental health scales.
If you instead adopted a qualitative approach, you might hold focus groups where small groups of students discuss their experiences with academic pressure and how it impacts their mental well-being. Transcripts from these sessions could be analyzed to identify recurring themes.
Combining qualitative and quantitative approaches in mixed methods research enables researchers to not only identify statistical patterns but also understand why and how they occur. However, combining qualitative and quantitative data can be complicated.
Types of mixed methods research designs
Different types of mixed methods research designs vary in when they collect and combine qualitative and quantitative data. Four types of mixed methods research are summarized in the table below:
| Design | Steps | When to use |
|---|---|---|
| Convergent parallel |
|
When you want to collect qualitative and quantitative data separately, then describe how their respective results converge and diverge |
| Embedded |
|
When you want to use either a quantitative or qualitative approach and supplement your findings with additional methods but have limited time or resources |
| Explanatory sequential |
|
When you want to first obtain quantitative results and then explain your findings using qualitative methods |
| Exploratory sequential |
|
When you’re exploring a new area and need qualitative results to help develop questions and hypotheses before collecting quantitative data |
Advantages and disadvantages of mixed methods research
A major advantage of mixed methods research is that it leverages the complementary strengths and weaknesses of qualitative and quantitative approaches. However, this benefit is not without drawbacks.
Advantages of mixed methods research
- Best of both worlds: Mixed methods research lets you take advantage of the benefits of both qualitative and quantitative methods. Often, the strengths of one compensate for the weaknesses of the other.
- Holistic insight into a research question: Using multiple research approaches can provide a more comprehensive understanding of a topic. Additionally, triangulation (the combination of multiple data sources) can increase the validity of your work.
- Flexibility: When adopting a mixed methods approach, especially a sequential design, qualitative findings can inform the collection of quantitative data and vice versa. You have the ability to adjust your approach based on your findings.
Disadvantages of mixed methods research
- Resource intensive: Mixed methods research requires the collection and analysis of multiple types of data. This process requires significantly more time and money than using just one method.
- Requires understanding of several methodologies: To leverage multiple research methods, you must have a strong understanding of them. This level of expertise can take time to build. Working with an interdisciplinary team is a way to overcome this challenge.
- Handling conflicting findings: When collecting different types of data to explore the same research question, there is a risk that your results will not align. It’s important to be prepared for this outcome and to address any divergence or discrepancies when interpreting your findings.
Examples of mixed methods research
Consider the following example of how different types of mixed methods designs can be used to answer a research question.
Convergent parallel design: The team could administer a survey to a group of telemedicine patients to examine health outcomes and how they rate their telemedicine experience (quantitative data). They could also run focus groups with a subset of patients (qualitative data). Both sets of results could be examined to understand themes common to patients with positive experiences and health outcomes.
Embedded design: The researchers decide to focus on quantitative health outcomes (e.g., blood pressure, medication adherence, and quality of life scores) for patients in the community. However, they supplement this information with open-ended survey questions administered to patients to better understand their experiences (qualitative data). Though the emphasis of this study is the quantitative findings, the qualitative data may offer additional insight into why the program is or is not effective.
Explanatory sequential design: The researchers begin by collecting quantitative health outcomes. Once they obtain this data, they observe that many patients with poor quantitative health outcomes are senior citizens. They next conduct interviews with patients in this demographic to better understand barriers they face in using the telemedicine program (qualitative data).
Exploratory sequential design: To understand factors that influence patients’ likelihood to use the telemedicine program, the researchers first run focus groups to understand any unexpected challenges or benefits (qualitative data). They use the results to create a survey that asks patients to rate the importance of various factors they’ve identified (quantitative data).
Frequently asked questions about mixed methods research
- What is triangulation in qualitative research?
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Triangulation involves using a combination of data or techniques to answer a research question. Triangulation can help you confirm the validity of your findings. This can be helpful in qualitative research, which is often subjective and vulnerable to bias.
Types of triangulation include the following:
- Data triangulation: uses data from different sources
- Investigator triangulation: has multiple people analyze data
- Theory triangulation: uses different theoretical frameworks to analyze data
- Methodological triangulation: uses different approaches to study the same phenomenon
- How do I analyze qualitative data?
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Qualitative data are generally narrative in nature. They may include interview transcripts or experimenter observations. Different approaches exist to analyze qualitative data, but common steps are as follows:
- Organize the data
- Code the data, sorting it into relevant categories
- Extract and interpret key ideas
Common qualitative data analysis techniques include content analysis, thematic analysis, and discourse analysis.
- What are some mixed methods research questions?
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Mixed methods research questions combine qualitative methods and quantitative methods to answer a research question. Examples of mixed methods research questions include the following:
- How does the proximity of student housing to college campuses (quantitative) relate to student perceptions of school culture (qualitative)?
- To what extent do air pollution levels (quantitative) correspond to residents’ perception of air quality (qualitative) in urban areas?
- What barriers do community members describe to accessing mental health services (qualitative), and how do these barriers correlate with use of these services within this community (quantitative)?
- What are the types of mixed methods research designs?
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The four main types of mixed methods research designs differ in when the quantitative and qualitative data are collected and analyzed:
- Convergent parallel design: Qualitative and quantitative data are collected and analyzed simultaneously and analyzed separately. The results are then compared, and similarities and dissimilarities between the findings are discussed.
- Embedded design: Either qualitative methods or quantitative methods are the focus of a study, and additional methods are used to support these main findings.
- Explanatory sequential design: Quantitative data are first collected and analyzed, then the results or patterns are explained using qualitative methods.
- Exploratory sequential design: Qualitative data are first collected and analyzed, then emergent themes are explored in more detail using quantitative methods.
- What is data collection?
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Data collection is the process of gathering data (measurements, observations, and other information) to answer a research question. Though many different methods of data collection exist, all are systemic and follow a procedure defined before data collection begins. Data can be qualitative or quantitative.
