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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 (social science)|triangulation]]) is now routinely advocated by most 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 all good research.
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 (social science)|triangulation]]) is now routinely advocated by most 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 all 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.
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'') only one analytic interest is pursued. In a ''mixed approach design (MAD)'' two or more analytic interests are pursued. NOTE: a mixed 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.
In a ''single approach design'' (''SAD'') only one analytic interest is pursued. In a ''mixed approach design (MAD)'' two or more analytic interests are pursued. NOTE: a mixed 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.

Revision as of 20:48, 12 November 2013

Multimethodology, mixed methods research, compatibility thesis or pragmatist paradigm is an approach to professional research that combines the collection and analysis of quantitative and qualitative data.[1]

The term 'multimethodology' appears to be more widely used in operations research than in other branches of social science.

This approach has been gaining in popularity since the 1980s.[2]

Mixed methods research

There are two broad classes of research studies that are currently being labeled “mixed methods research”:

  1. single approach designs (SADs) in which additional qualitative and/or quantitative strategies are employed to enhance research quality; and
  2. mixed approach designs (MADs). These definitions require that a distinction be made between research strategies and research approaches.

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 most 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 all 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) only one analytic interest is pursued. In a mixed approach design (MAD) two or more analytic interests are pursued. NOTE: a mixed 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.

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. "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.

Desirability

The case for multimethodology as a strategy for intervention and/or research is based on four observations:

  1. Narrow views of the world are often misleading, so approaching a subject from different perspectives or paradigms may help to gain a holistic perspective
  2. 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
  3. Many existing practices already combine methodologies to solve particular problems, yet they have not been theorised sufficiently
  4. Multimethodology fits well with postmodernism

Feasibility

There are also some hazards to multimethodological approaches. Some of these problems include:

  1. 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.
  2. 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.
  3. 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.

Computer Assisted Mixed Methods Research Analysis Software

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:

  1. MAXQDA is a qualitative data analysis and mixed methods software developed by VERB Software. Consult. Sozialforschung GmbH.
  2. Dedoose is a Web Based Qualitative Analysis application and Mixed Methods research tool developed by professors from UCLA, and is the successor to EthnoNotes.[3][4]
  3. EthnoNotes[4][5]
  4. QDA Miner[6] is a qualitative data analysis and mixed methods software developed by Provalis Research.[7]

Conclusion

Multimethodology is desirable and feasible because it gives a more complete view, and because the requirement during the different phases of the 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 develop an instrument or to identify variables to test in a later quantitative study. You engage in a mixed methods study when you want to follow up a quantitative study with a qualitative one to obtain more detailed specific information.

Criticisms

Multimethodology is criticized by the adherents of incompatibility thesis - particularly post-structuralist and post-modernists. Its critics argue that multimethodology is inherently wrong because quantitative and qualitative research paradigms should not be mixed.[2]

See also

References

  1. ^ Creswell, John (2004). Educational Research: Planning, Conducting, and Evaluating Quantitative and Qualitative Research. Prentice Hall. ISBN 978-0-13-112790-6.
  2. ^ a b Onwuegbuzie, Anthony and Leech, 2005
  3. ^ http://www.dedoose.com
  4. ^ a b Lieber, E., & Weisner T. S. (2010). Meeting the Practical Challenges of Mixed Methods Research. In A. Tashakkori & C. Teddlie (Eds.), Mixed Methods in Social & Behavioral Research 2nd Ed., (pp. 559-611). Thousand Oaks, CA; SAGE Publications.
  5. ^ Lieber, E., Weisner, T. S., & Presley, M. (2003). EthnoNotes: An Internet-Based Field Note Management Tool. Field Methods, 15(4), 405-425.
  6. ^ Lewis, QDA Miner 2.0: Mixed-Model Qualitative Data Analysis Software. Field Methods 19:87-108
  7. ^ http://www.provalisresearch.com

Further reading

  • Andres, Lesley (2012). "Designing and Doing Survey Research". London: Sage. Survey research from a mixed methods perspective.
  • Brannen, Julia. 2005. “Mixing Methods: The Entry of Qualitative and Quantitative Approaches into the Research Process.” International Journal of Social Research Methodology 8:173-184.
  • Mingers J., Brocklesby J., "Multimethodology: Towards a Framework for Mixing Methodologies", Omega, Volume 25, Number 5, October 1997, pp. 489–509 (21)
  • Niglas, Katrin. 2004. "The Combined Use of Qualitative and Quantitative Methods in Educational Research." http://www.tlulib.ee/files/arts/95/nigla32417030233e06e8e5d471ec0aaa32e9.pdf
  • 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).

  • Lowenthal, P. R., & Leech, N. (2009). Mixed research and online learning: Strategies for improvement. In T. T. Kidd (Ed.), Online education and adult learning: New frontiers for teaching practices (pp. 202–211). Hershey, PA: IGI Global.