Article by Patrick Fiorenza, RMS Director of Research Analytics
One of the most popular blog posts on the RMS site describes the differences between qualitative and quantitative research. What if I told you there was a third approach to research? Mixed methods is a common approach in the program evaluation world to leverage the benefits of both qualitative and quantitative data.
Mixed methods and mixed modes are similar, but they are distinct in that mixed methods brings clear frameworks to properly combine data (see below). The definition of mixed methods has evolved substantially throughout the years, and although multiple definitions exist, Creswell’s (2015) definition provides the most succinct explanation:
An approach to research in the social, behavioral, and health sciences in which the investigator gathers both quantitative (closed-ended) and qualitative (open-ended) data, integrates the two, and then draws interpretations based on the combined strengths of both sets of data to understand research problems (p.124 ).
Creswell is one of my go-to’s for mixed methods research. I like this definition because he points out some key words.
- Quantitative: Think of a basic survey, with your scales, items, ordinal and categorical variables, etc.
- Qualitative: Think of an interview and the raw transcripts, or even open-ended responses on a survey.
- Integrates: the key to mixed methods is true integration of data, not simply running two similar studies with an interview and survey. Many studies claim to be mixed methods, but miss the mark because there isn’t true integration of data.
- Draws: Creswell talks about the strengths of qualitative and quantitative, but another real benefit is that mixed methods enhances your findings, as you can use qualitative to clarify quantitative data, or quantitative data to confirm qualitative.
Below are the primary types of mixed methods designs presented by Creswell and Plano Clark (2011). These designs are frequently referenced in the literature, and although there are multiple scholars discussing research designs, Creswell and Plano Clark’s models serve as a starting point to build a theoretical framework in a study.
Convergent Parallel Design. This design is sometimes referred simply as a “parallel design.” It requires that the quantitative and qualitative strands of research are conducted independently, and the results are brought together during the final interpretation (Creswell, 2011, p. 69).
Explanatory sequential design. In this design, the first phase (both collection and analysis of data) is quantitative, followed by the collection of qualitative data, used to help explain the quantitative results (Creswell, 2011, p. 69).
Exploratory sequential design. With this design, the first phase of the research is qualitative (data collection and analysis), followed by quantitative data to “test or generalize” the initial qualitative findings (Creswell, 2011, p. 69).
Embedded design. This design presents a traditional qualitative or quantitative framework, and another method is used to “enhance the overall design” (Creswell, 2011, p. 70).
Transformative design. According to Creswell, in this design, “a transformative theoretical framework, e. g. feminism or critical race theory, shapes the interaction, priority, timing and mixing of the qualitative and quantitative strand” (p.70).
Multiphase design. The multiphase design “is an intricate mixed-method design where two or more phases, or both a sequential and concurrent design, are combined within a single study” (Creswell, 2011, p.70).
The real magic of mixed-methods research is learning how to build upon foundational designs, that clearly align with a study’s research questions. The methodology section of the evaluation plan is the spot to clearly explain the design and reasons for its selection, explaining that the design was purposefully and thoughtfully selected to meet the objectives of the study.
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About the Author – Patrick Fiorenza
Patrick brings years of market research experience to the RMS Research Analytics team. His preliminary focus encompasses designing, implementing, gathering, and analyzing results from proven research methods created to obtain credible data to help guide decision-making across a variety of industries.
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