Mixed methods research relies on multiple research methods, data sets, or theoretical approaches to assemble a more comprehensive picture of a concept or phenomenon. Especially in
qualitative research or social science research, any set of findings can be considered more credible if they are supported with evidentiary data that comes from different perspectives.
Method triangulation
Method triangulation involves combining qualitative and quantitative methods together to study different but related aspects. In this respect, quantitative and qualitative research study the same phenomenon to lend support to each method's findings. Note that the goal of triangulated mixed methods research is not to simply use multiple methods to arrive at the same answer but to generate a better understanding of a phenomenon that one method alone cannot sufficiently capture.
In this case, method triangulation is a useful concept for a mixed methods researcher because it requires them to acknowledge the strengths and weaknesses of each particular research method. At scale, quantitative methods cannot capture concepts that are unquantifiable (e.g., beauty, convenience). In contrast,
qualitative methods often do not conduct data collection at scales necessary to make generalizations about phenomena. Integrating quantitative and qualitative research components under the same mixed methods design ensures a comprehensive examination of a phenomenon that one method alone cannot accomplish.
Ethnography provides ample opportunities to pursue method triangulation. Data collection in ethnographic research often involves collecting qualitative data through
observations and
interviews. In contrast, data analysis can assess quantitative data by identifying patterns in behavior and perspectives and determining their frequencies.
Another example is a mixed methods study that examines patient outcomes at a hospital. Initial qualitative results might come from field notes from observations of doctors and nurses and interview data with patients. The quantitative findings might come from conducting a statistical analysis of the money and resources used for each patient observed or interviewed to determine whether the expenditure is commensurate with the patient outcomes achieved.
A standalone quantitative study might look only at the financial aspects of health care, while a qualitative study might do better at examining the social and emotional aspects. Conducting both of these studies in tandem can help researchers determine actionable insights for streamlining health care services while maintaining satisfactory standards of care.
Data triangulation
Mixed methods research usually depends on method triangulation, but it's important to identify other forms of triangulation that can strengthen the findings in any research. A study that relies on data triangulation looks at different sets of data. For example, an educational researcher might examine student outcomes at different schools or at the same school but at different times. Data triangulation is useful in affirming that the findings in one context are applicable across other contexts.
Theory triangulation
Another kind of triangulation less commonly associated with mixed methods research deals with analyzing data using different theories. A sequential research design, for example, may use the initial quantitative results from a survey study to generate a
conceptual framework for the analysis of a subsequent qualitative study. At the same time, existing theories may also be employed in that analysis to compare and contrasts the kinds of insights and outcomes that each may produce.
Theory generation in mixed methods research
Many forms of research seek to generate or develop a
theoretical framework to understand the object of inquiry. There are two common forms of theory generation, and both can manifest in the
research questions that are posed in any study.
Research questions can either be exploratory, which try to define or gain a greater understanding of a phenomenon, or confirmatory, which try to test a theory or
hypothesis regarding that phenomenon. With some exceptions,
exploratory research questions call for collecting
qualitative data, while confirmatory research questions require
quantitative data.
In that respect, common mixed methods designs combine qualitative and quantitative components to generate a theory and either strengthen or challenge that theory, respectively. To understand what that theory generation looks like when employing mixed methods, we need to examine some of the different kinds of mixed methods research designs.
