Multimethodology or multimethod research includes the use of more than one method of data collection or research in a research study or set of related studies. Mixed methods research is more specific in that it includes the mixing of qualitative and quantitative data, methods, methodologies, and/or paradigms in a research study or set of related studies. One could argue that mixed methods research is a special case of multimethod research. Another applicable, but less often used label, for multi or mixed research is methodological pluralism. All of these approaches to professional and academic research emphasize that monomethod research can be improved through the use of multiple data, methods, Research,methodologies, perspectives, standpoints, and paradigms. 
The term 'multimethodology' was used starting in the 1980s and in the 1989 book Multimethod Research: A Synthesis of Styles by John Brewer and Albert Hunter (Sage Publications). During the 1990s and currently, the term 'mixed methods research' has become more popular for this research movement in the behavioral, social, business, and health sciences. This pluralistic research approach has been gaining in popularity since the 1980s.
Multi and mixed methods research
There are three broad classes of research studies that are currently being labeled “mixed methods research” (Johnson, Onwuegbuzie, & Turner, 2007)
- Quantitatively driven approaches/designs in which the research study is, at its core, a quantitative study with qualitative data/method added to supplement and improve the quantitative study by providing an added value and deeper, wider, and fuller or more complex answers to research questions; quantitative quality criteria are emphasized but high quality qualitative data also must be collected and analyzed;
- Qualitatively driven approaches/designs in which the research study is, at its core, a qualitative study with quantitative data/method added to supplement and improve the qualitative study by providing an added value and deeper, wider, and fuller or more complex answers to research questions; qualitative quality criteria are emphasized but high quality quantitative data also must be collected and analyzed (Hesse-Biber, 2010);
- Interactive or equal status designs in which the research study equally emphasizes (interactively and through integration) quantitative and qualitative data, methods, methodologies, and paradigms. This third design is often done through the use of a team composed of an expert in quantitative research, an expert in qualitative research, and an expert in mixed methods research to help with dialogue and continual integration. In this type of mixed study, quantitative and qualitative and mixed methods quality criteria are emphasized. This use of multiple quality criteria is seen in the concept of multiple validities legitimation (Johnson & Christensen, 2014; Onwuegbuzie & Johnson, 2006). Here is a definition of this important type of validity or legitimation: Multiple validities legitimation "refers to the extent to which the mixed methods researcher successfully addresses and resolves all relevant validity types, including the quantitative and qualitative validity types discussed earlier in this chapter as well as the mixed validity dimensions. In other words, the researcher must identify and address all of the relevant validity issues facing a particular research study. Successfully addressing the pertinent validity issues will help researchers produce the kinds of inferences and meta-inferences that should be made in mixed research"(Johnson & Johnson, 2014; page 311).
- Mixed priority designs in which the principal study results derive from the integration of qualitative and quantitative data during analysis (Creamer, 2017).
One major similarity between mixed methodologies and qualitative and quantitative taken separately is that researchers need to maintain focus on the original purpose behind their methodological choices. A major difference between the two however, is the way some authors differentiate the two, proposing that there is logic inherent in one that is different from the other. Creswell (2009) points out that in a quantitative study the researcher starts with a problem statement, moving on to the hypothesis and null hypothesis, through the instrumentation into a discussion of data collection, population, and data analysis. Creswell proposes that for a qualitative study the flow of logic begins with the purpose for the study, moves through the research questions discussed as data collected from a smaller group and then voices how they will be analysed.
A research strategy is a procedure for achieving a particular intermediary research objective — such as sampling, data collection, or data analysis. We may therefore speak of sampling strategies or data analysis strategies. The use of multiple strategies to enhance construct validity (a form of methodological triangulation) is now routinely advocated by methodologists. In short, mixing or integrating research strategies (qualitative and/or quantitative) in any and all research undertaking is now considered a common feature of good research.
A research approach refers to an integrated set of research principles and general procedural guidelines. Approaches are broad, holistic (but general) methodological guides or roadmaps that are associated with particular research motives or analytic interests. Two examples of analytic interests are population frequency distributions and prediction. Examples of research approaches include experiments, surveys, correlational studies, ethnographic research, and phenomenological inquiry. Each approach is ideally suited to addressing a particular analytic interest. For instance, experiments are ideally suited to addressing nomothetic explanations or probable cause; surveys — population frequency descriptions, correlations studies — predictions; ethnography — descriptions and interpretations of cultural processes; and phenomenology — descriptions of the essence of phenomena or lived experiences.
In a single approach design (SAD)(also called a "monomethod design") only one analytic interest is pursued. In a mixed or multiple approach design (MAD) two or more analytic interests are pursued. NOTE: a multiple approach design may include entirely “quantitative” approaches such as combining a survey and an experiment; or entirely “qualitative” approaches such as combining an ethnographic and a phenomenological inquiry, and a mixed approach design includes a mixture of the above (e.g., a mixture of quantitative and qualitative data, methods, methodologies, and/or paradigms).
A word of caution about the term “multimethodology”. It has become quite common place to use the terms "method" and "methodology" as synonyms (as is the case with the above entry). However, there are convincing philosophical reasons for distinguishing the two. "Method" connotes a way of doing something — a procedure (such as a method of data collection). "Methodology" connotes a discourse about methods — i.e., a discourse about the adequacy and appropriateness of particular combination of research principles and procedures. The terms methodology and biology share a common suffix "logy." Just as bio-logy is a discourse about life — all kinds of life; so too, methodo-logy is a discourse about methods — all kinds of methods. It seems unproductive, therefore, to speak of multi-biologies or of multi-methodologies. It is very productive, however, to speak of multiple biological perspectives or of multiple methodological perspectives.
The case for multimethodology or mixed methods research as a strategy for intervention and/or research is based on four observations:
- Narrow views of the world are often misleading, so approaching a subject from different perspectives or paradigms may help to gain a holistic perspective with hi.
- There are different levels of social research (i.e.: biological, cognitive, social, etc.), and different methodologies may have particular strengths with respect to one of these levels. Using more than one should help to get a clearer picture of the social world and make for more adequate explanations.
- Many existing practices already combine methodologies to solve particular problems, yet they have not been theorised sufficiently.
- Multimethodology fits well with pragmatism.
There are also some hazards to multimethodological or mixed methods research approaches. Some of these problems include:
- Many paradigms are at odds with each other. However, once the understanding of the difference is present, it can be an advantage to see many sides, and possible solutions may present themselves.
- Multimethod and mixed method research can be undertaken from many paradigmatic perspectives, including pragmatism, dialectial pluralism, critical realism, and constructivism.
- Cultural issues affect world views and analyzability. Knowledge of a new paradigm is not enough to overcome potential biases; it must be learned through practice and experience.
- People have cognitive abilities that predispose them to particular paradigms. The logical thinker can more easily understand and use quantitative methodologies. It is easier to move from quantitative to qualitative, and not the reverse.
A few qualitative research analysis software applications support some degree of quantitative integration, and the following software or web applications focus on mixed methods research:
- Dedoose is a web-based qualitative analysis application and mixed methods research tool developed by professors from UCLA, and is the successor to EthnoNotes.
- MAXQDA is a qualitative data analysis and mixed methods software developed by VERBI Software. Consult. Sozialforschung GmbH. Mixed methods functionality includes guided creation for Joint Displays.
- NVivo is qualitative and mixed methods data analysis software developed by QSR International.
- QDA Miner is a qualitative data analysis and mixed methods software developed by Provalis Research.
Multimethodology and mixed methods research are desirable and feasible because they provide a more complete view, and because the requirement during the different phases of an intervention (or research project) make very specific demands on a general methodology. While it is demanding, it is more effective to choose the right tool for the job at hand.
It can be used when you want to build from one phase of research to another. You may first want to explore the data qualitatively to identify help in the development an instrument or to identify concepts/variables to test in a later quantitative study or phase of a single study. You engage in a mixed methods study when you want to construct a quantitatively-driven design, a qualitatively-driven design, or an interactive/equal-status design. Each of these come with advantages and disadvantages. For more information on designing multiple and mixed methods research studies see the following design typologies and other (anti-typology): Brewer & Hunter (2006); Creamer (2017); Creswell & Plano Clark (2011); Greene (2007); Guest (2013); Johnson & Christensen (2014); Morgan (2014); Morse & Niehaus (2009); Muskat et al. (2012); and Teddlie & Tashakkori (2009).
Multimethodology is criticized by the adherents of incompatibility thesis - particularly post-structuralist and post-modernists. Its critics argue that mixed methods research is inherently wrong because quantitative and qualitative approach represent different and inherently incompatible research paradigms.
- Perestroika Movement (political science)
- Post-autistic economics
- Computer-assisted qualitative data analysis software
- Creswell, J. W. 2004
- Johnson, R. B. & Christensen, J. B., 2014
- Tashakkori, Abbas; Teddlie, Charles (2010). Mixed Methods in Social & Behavioral Research. Sage. ISBN 978-1412972666.
- Onwuegbuzie, Anthony and Leech, 2005
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- Brewer, J., & Hunter, A. (2006). Foundations of multimethod research: Synthesizing styles. Thousand Oaks, CA: Sage.
- Creamer, E. G. (2017). An introduction to fully integrated mixed methods research. Thousand Oaks, CA:Sage.
- Creswell, J. W., & Plano Clark, V. L. (2011). Designing and conducting mixed methods research. Los Angeles, CA: Sage.
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- Morse, J. M., & Niehaus, L. (2009). Mixed methods design: Principles and procedures. Left Coast Press.
- Muskat, M., Blackman, D., & Muskat, B. (2012). Mixed methods: Combining expert interviews, cross-impact analysis and scenario development. Electronic Journal of Business Research Methods, 10(1): 9–21. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2269508
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- Onwuegbuzie, A. J., & Johnson, R. B. (2006). The “Validity” Issue in Mixed Methods Research. Research in the Schools, 13(1), 48-63.
- Onwuegbuzie, Anthony and Leech, Nancy; 2005. “Taking the “Q” Out of Research: Teaching Research Methodology Courses Without the Divide Between Quantitative and Qualitative Paradigms.” Quality and Quantity 39:267-296.
- Schram, Sanford F., and Brian Caterino, eds., Making Political Science Matter: Debating Knowledge, Research, and Method (New York: New York University Press, 2006).
- Teddlie, C., & Tashakkori, A. (2009). Foundations of mixed methods research: Integrating quantitative and qualitative approaches in the social and behavioral sciences. Thousand Oaks, CA: Sage.