Victor Lofgreen, Ph.D.

As practitioner researchers, we find ourselves conducting research in organizational and community settings. Doing applied research in these settings can present both opportunities and problems. Research projects in settings exclusively established for research offer more control over access to data and the type of data available. A mixed research model may be the answer to the research design question.

Choosing a research method or model is central to developing a good research project. The typical methodological choices are to design a quantitative, qualitative, or mixed-model design. Sometimes we are able to choose from these options. Other times the research model may emerge from the nature of the research question, the types of data available, and the kind of analysis we expect to use.

Tashakkori and Teddlie (1998) developed a helpful tool to use when choosing what research method or model to use for a study. In their book Mixed Methodology Combining Qualitative and Quantitative Approaches, they provide a rationale for the selection of a research design based on three elements of the research process:

1. Is the purpose of the research confirmatory or exploratory?
2. Are the data available qualitative or quantitative?
3. Does the desired analysis call for a narrative or statistical inference?

The research model matrix they created from this view gives six types of research models from which to choose. Their taxonomy allows for data to be collected in either form and then to be analyzed directly or converted to another form for analysis (Tashakkori & Teddlie, 1998, pp. 57–58).

Rather than look at qualitative and quantitative research models as either/or choices, they have created a continuum of research models that begins with the classical quantitative experimental model and proceeds to the purely qualitative case study. They then created a classification of design models that include both quantitative and qualitative features in combination, according to the purpose of the research project.

This approach provides for the conversion of quantitative measures to qualitative characteristics or qualitative characteristics to quantitative measures for analysis. Using this approach, they provide a rationale for design selection that is tailored for a particular study.

Using this perspective in research design, it is possible to mix the purpose, data collection, and data types in ways that produce flexibility that might otherwise not be apparent. For researchers working in settings that are restricted by institutional constraints or in community settings that preclude the manipulation of variables, the use of a mixed research model may enlarge the field of tools available.

Table 1. Example of Mixed Research Models: A Priori Theory or Model Confirmation

Note: Type II is considered a mixed model because qualitative studies are traditionally used for exploratory purposes. Here the model is used for confirmation of an a priori model or theory (Tashakkori & Teddlie, 1998, pp. 139–144).

Table 2. Mixed-Method Research Models: Exploratory Studies

Note: Type III is considered a mixed model because quantitative analysis is used for a priori model or theory confirmation, but is used here as an exploratory research model (Tashakkori & Teddlie, 1998, pp. 145–148).

Reference

Tashakkori, A., & Teddlie, C., (1998). Mixed methodology combining qualitative and quantitative approaches. Thousand Oaks, CA: Sage Publications.

QUESTIONS? COMMENTS?