Mixed Methods Design

Mixed methods is a research orientation that possesses unique purposes and techniques. It [Page 813]integrates techniques from quantitative and qualitative paradigms to tackle research questions that can be best addressed by mixing these two traditional approaches. As long as 40 years ago, scholars noted that quantitative and qualitative research were not antithetical and that every research process, through practical necessity, should include aspects of both quantitative and qualitative methodology. In order to achieve more useful and meaningful results in any study, it is essential to consider the actual needs and purposes of a research problem to determine the methods to be implemented. The literature on mixed methods design is vast, and contributions have been made by scholars from myriad disciplines in the social sciences. Therefore, this entry is grounded in the work of these scholars. This entry provides a historical overview of mixed methods as a paradigm for research, establishes differences between quantitative and qualitative designs, shows how qualitative and quantitative methods can be integrated to address different types of research questions, and illustrates some implications for using mixed methods. Though still new as an approach to research, mixed methods design is expected to soon dominate the social and behavioral sciences.

The objective of social science research is to understand the complexity of human behavior and experience. The task of the researcher, whose role is to describe and explain this complexity, is limited by his or her methodological repertoire. As tradition shows, different methods often are best applied to different kinds of research. Having the opportunity to apply various methods to a single research question can broaden the dimensions and scope of that research and perhaps lead to a more precise and holistic perspective of human behavior and experience. Research is not knowledge itself, but a process in which knowledge is constructed through step-by-step data gathering.

Data are gathered most typically through two distinct classical approaches—qualitative and quantitative. The use of both these approaches for a single study, although sometimes controversial, is becoming more widespread in social science. Methods are really “design” components that include the following: (a) the relationship between the researcher and research “subjects,” (b) details of the experimental environment (place, time, etc.), (c) sampling and data collection methods, (d) data analysis strategies, and (e) knowledge dissemination. The design of a study thus leads to the choice of method strategy. The framework for a study, then, depends on the phenomenon being studied, with the participants and relevant theories informing the research design. Most study designs today need to include both quantitative and qualitative methods for gathering effective data and can thereby incorporate a more expansive set of assumptions and a broader worldview.

Mixing methods (or multiple-methods design) is generally acknowledged as being more pertinent to modern research than using a single approach. Quantitative and qualitative methods may rely more on single data collection methods. For example, whereas a quantitative study may rely on surveys for collecting data, a qualitative study may rely on observations or open-ended questions. However, it is also possible that each of these approaches may use multiple data collection methods. Mixed methods design “triangulates” these two types of methods. When these two methods are used within a single research study, different types of data are combined to answer the research question—a defining feature of mixed methods. This approach is already standard in most major designs. For example, in social sciences, interviews and participant observation form a large part of research and are often combined with other data (e.g., biological markers).

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