How do you use mixed methods in data analysis?

1 What are mixed methods?

Mixed methods are a type of data analysis that combines quantitative and qualitative approaches. Quantitative methods use numerical data and statistical techniques to measure, compare, or test variables. Qualitative methods use non-numerical data and interpretive techniques to explore, understand, or describe phenomena. Mixed methods use both types of data and methods to address different aspects of a research question or problem.

2 Why use mixed methods?

Mixed methods can offer several advantages for data analysis, such as enhancing the validity and reliability of your findings by triangulating or corroborating data from different sources or perspectives. This approach can provide a more comprehensive and nuanced picture of your phenomenon of interest by capturing its complexity and diversity. Moreover, mixed methods can address different types of research questions or objectives that require both quantitative and qualitative data and methods, as well as generate new insights or hypotheses by integrating or comparing data from different methods or paradigms.

3 How to design a mixed methods study?

When designing a mixed methods study, careful planning and design is essential to ensure that the quantitative and qualitative components are effectively aligned and integrated. There are various approaches to consider, such as the convergent, explanatory, exploratory, or embedded design. For example, the convergent design involves collecting and analyzing quantitative and qualitative data separately before comparing or merging them to draw conclusions. The explanatory design involves collecting and analyzing quantitative data first before using qualitative data to explain or explore the results further. The exploratory design involves collecting and analyzing qualitative data first before using quantitative data to test or generalize the findings. Lastly, the embedded design involves embedding one type of data within another type of data or method, such as using qualitative data to supplement or enhance a quantitative experiment.

4 How to collect mixed methods data?

The data collection methods you choose for your mixed methods study depend on your research question, design, and resources. You can use existing or secondary data sources, such as surveys, databases, documents, or media, or you can collect your own or primary data sources, such as interviews, observations, or experiments. You can also use mixed methods data collection tools, such as questionnaires with open-ended and closed-ended questions, focus groups with structured and unstructured activities, or case studies with quantitative and qualitative data.

5 How to analyze mixed methods data?

The data analysis methods you use for your mixed methods study depend on your research question, design, and data types. You can use quantitative data analysis methods, such as descriptive statistics, inferential statistics, or regression models, to summarize, test, or predict your numerical data. You can use qualitative data analysis methods, such as thematic analysis, content analysis, or discourse analysis, to code, categorize, or interpret your non-numerical data. You can also use mixed methods data analysis methods, such as meta-analysis, cross-case analysis, or joint display, to integrate, synthesize, or compare your quantitative and qualitative data.

6 How to report mixed methods findings?

The reporting of your mixed methods findings depends on your research question, design, and audience. Different formats and styles such as reports, articles, presentations, or visualizations can be used to communicate your findings. Additionally, various strategies can be employed to present your findings. For instance, a narrative approach uses text to describe and discuss your findings, with quotes, tables, or charts adding illustration. Alternatively, a visual approach employs graphs, diagrams, or maps to display and explain your findings while text provides context or interpretation. Finally, an interactive approach uses digital tools or platforms to share and engage with your findings by utilizing text, audio, or video to provide information or feedback.

7 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?