The Cambridge Handbook of Research Methods and Statistics for the Social and Behavioral Sciences Volume 2: Performing Research
Book contents
- The Cambridge Handbook of Research Methods and Statistics for the Social and Behavioral Sciences
- Cambridge Handbooks in Psychology
- The Cambridge Handbook of Research Methods and Statistics for the Social and Behavioral Sciences
- Copyright page
- Dedication
- Contents
- Figures
- Tables
- Contributors
- Preface
- Part I Quantitative Data Collection Sources
- 1 Student Samples in Research
- 2 Mechanical Turk: A Versatile Tool in the Behavioral Scientist’s Toolkit
- 3 Social Media Research
- 4 Prolific: Crowdsourcing Academic Online Research
- 5 Field Research
- 6 Organizational Research
- 7 Integrating Culture in Research
- 8 Mixed Methods and Multimethod Research
- Part II Important Methodological Considerations
- Part III Self-Report Measures
- Part IV Behavioral Measures
- Part V Physiological Measures
- Part VI Qualitative Data Collection Sources
- Index
- References
8 - Mixed Methods and Multimethod Research
from Part I - Quantitative Data Collection Sources
Published online by Cambridge University Press: 12 December 2024
Book contents
- The Cambridge Handbook of Research Methods and Statistics for the Social and Behavioral Sciences
- Cambridge Handbooks in Psychology
- The Cambridge Handbook of Research Methods and Statistics for the Social and Behavioral Sciences
- Copyright page
- Dedication
- Contents
- Figures
- Tables
- Contributors
- Preface
- Part I Quantitative Data Collection Sources
- 1 Student Samples in Research
- 2 Mechanical Turk: A Versatile Tool in the Behavioral Scientist’s Toolkit
- 3 Social Media Research
- 4 Prolific: Crowdsourcing Academic Online Research
- 5 Field Research
- 6 Organizational Research
- 7 Integrating Culture in Research
- 8 Mixed Methods and Multimethod Research
- Part II Important Methodological Considerations
- Part III Self-Report Measures
- Part IV Behavioral Measures
- Part V Physiological Measures
- Part VI Qualitative Data Collection Sources
- Index
- References
Summary
This chapter explains how researchers can design studies that include multiple methods. It starts by defining multiple-methods research as bringing together multiple perspectives at the methodological and other levels to obtain a deeper and more inclusive understanding of a phenomenon (and, in the end, to make a better-informed decision) than would be possible using one method alone. Using four real-life examples, Part I of the chapter shows the four consecutive steps of multiple-methods design: including multiple perspectives, exploring them, integrating their conclusions, and using this integrated conclusion to make a decision in practice. Part II shows that multiple-methods research is emergent and discusses the most important of these emergent elements: emerging aspects, focusing, searching for explanations, emerging data, and emerging subgroups. Part III discusses concepts that are relevant to combining qualitative and quantitative data sets: meaningful connections, purposes of mixing, theoretical drive, timing, and fully integrated research designs. The chapter concludes with recommendations for research with multiple methods.
- Type
- Chapter
- Information
- The Cambridge Handbook of Research Methods and Statistics for the Social and Behavioral SciencesVolume 2: Performing Research, pp. 163 - 186Publisher: Cambridge University PressPrint publication year: 2024
References
Anguera, M. T., Blanco-Villaseñor, A., Losada, J. L., Sánchez-Algarra, P., & Onwuegbuzie, A. J. (2018). Revisiting the difference between mixed methods and multimethods: Is it all in the name? Quality & Quantity, 52(6), 2757–2770. https://doi.org/10.1007/s11135-018-0700-2CrossRefGoogle Scholar
Bazeley, P. (2018). Integrating Analyses in Mixed Methods Research. SAGE Publications.CrossRefGoogle Scholar
Bazeley, P., & Kemp, L. (2012). Mosaics, triangles, and DNA: Metaphors for integrated analysis in mixed methods research. Journal of Mixed Methods Research, 6, 55–72. https://doi.org/10.1177/1558689811419514CrossRefGoogle Scholar
Bryman, A. (2006). Integrating quantitative and qualitative research: How is it done? Qualitative Research, 6(1), 97–113. https://doi.org/10.1177/1468794106058877CrossRefGoogle Scholar
Bryman, A. (2007). Barriers to integrating quantitative and qualitative research. Journal of Mixed Methods Research, 1(1), 8–22. https://doi.org/10.1177/2345678906290531CrossRefGoogle Scholar
Bryman, A. (2008). Why do researchers integrate/combine/mesh/blend/mix/merge/fuse quantitative and qualitative research? In Bergman, M. M. (ed.), Advances in Mixed Methods Research (pp. 87–100). SAGE Publications. https://doi.org/10.4135/9780857024329.d9Google Scholar
Clark, A. (2005). Ways of seeing: Using the Mosaic approach to listen to young children’s perspectives. In Clark, A., Kjørholt, A. T., & Moss, P. (eds.), Beyond Listening: Children’s Perspectives on Early Childhood Services (pp. 29–49). Policy Press.Google Scholar
Clark, A., & Moss, P. (2005). Spaces to Play: More Listening to Young Children Using the Mosaic Approach. National Children’s Bureau.Google Scholar
Creamer, E. G. (2018). An Introduction to Fully Integrated Mixed Methods Research. SAGE Publications.CrossRefGoogle Scholar
Creswell, J. W., & Plano Clark, V. L. (2018). Designing and Conducting Mixed Methods Research, 3rd ed. SAGE Publications.Google Scholar
Fetters, M. D., & Molina-Azorin, J. F. (2017). The journal of mixed methods research starts a new decade: The mixed methods research integration trilogy and its dimensions. Journal of Mixed Methods Research, 11(3), 291–307. https://doi.org/10.1177/1558689817714066CrossRefGoogle Scholar
Finlay, W. M. L., Rohleder, P., Taylor, N., & Culfear, H. (2015). “Understanding” as a practical issue in sexual health education for people with intellectual disabilities: A study using two qualitative methods. Health Psychology, 34(4), 328–338. https://doi.org/10.1037/hea0000128CrossRefGoogle ScholarPubMed
Greene, J. C. (2008). Is mixed methods social inquiry a distinctive methodology? Journal of Mixed Methods Research, 2(1), 7–22. https://doi.org/10.1177/1558689807309969CrossRefGoogle Scholar
Greene, J. C., Caracelli, V. J., & Graham, W. F. (1989). Toward a conceptual framework for mixed-method evaluation designs. Educational Evaluation and Policy Analysis, 11(3), 255–274. https://doi.org/10.2307/1163620CrossRefGoogle Scholar
Guest, G. (2013). Describing mixed methods research: An alternative to typologies. Journal of Mixed Methods Research, 7(2), 141–151. https://doi.org/10.1177/1558689812461179CrossRefGoogle Scholar
Guetterman, T. C., & Fetters, M. D. (2022). Data visualization in the context of integrated analyses. In Hitchcock, J. H. & Onwuegbuzie, A. J. (eds.), The Routledge Handbook for Advancing Integration in Mixed Methods Research (pp. 301–323). Routledge. https://doi.org/10.4324/9780429432828-6CrossRefGoogle Scholar
Ivankova, N. V. (2015). Mixed Methods Applications in Action Research: From Methods to Community Action. SAGE Publications.CrossRefGoogle Scholar
Ivankova, N. V., Creswell, J. W., & Stick, S. L. (2006). Using mixed-methods sequential explanatory design: From theory to practice. Field Methods, 18(1), 3–20. https://doi.org/10.1177/1525822x05282260CrossRefGoogle Scholar
Johnson, R. B., Onwuegbuzie, A. J., & Turner, L. A. (2007). Toward a definition of mixed methods research. Journal of Mixed Methods Research, 1(2), 112–133. https://doi.org/10.1177/1558689806298224CrossRefGoogle Scholar
Lee, Y.-J., & Greene, J. (2007). The predictive validity of an ESL placement test: A mixed methods approach. Journal of Mixed Methods Research, 1(4), 366–389. https://doi.org/10.1177/1558689807306148CrossRefGoogle Scholar
Maxwell, J. A. (2013). Qualitative Research Design: An Interactive Approach, 3rd ed. SAGE Publications.Google Scholar
Maxwell, J. A., & Loomis, D. M. (2003). Mixed methods design: An alternative approach. In Tashakkori, A. & Teddlie, C. (eds.), Handbook of Mixed Methods in Social & Behavioral Research (pp. 241–271). SAGE Publications.Google Scholar
Maxwell, J. A., & Mittapalli, K. (2010). Realism as a stance for mixed methods research. In Tashakkori, A. & Teddlie, C. (eds.), SAGE Handbook of Mixed Methods in Social & Behavioral Research, 2nd ed. (pp. 145–167). SAGE Publications.CrossRefGoogle Scholar
Mertens, D. M., Bazeley, P., Bowleg, L., Fielding, N., Maxwell, J., Molina-Azorin, J. F., & Niglas, K. (2016). The Future of Mixed Methods: A Five Year Projection to 2020. Mixed Methods International Research Association task force report. https://mmira.wildapricot.org/resources/Documents/MMIRA%20task%20force%20report%20Jan2016%20final.pdfGoogle Scholar
Morse, J. M., Bowers, B. J., Charmaz, K., Clarke, A. E., Corbin, J., & Porr, C. J. (eds.). (2021). Developing Grounded Theory: The Second Generation Revisited, 2nd ed. Routledge.CrossRefGoogle Scholar
Morse, J. M., & Niehaus, L. (2009). Mixed Method Design: Principles and Procedures. Left Coast Press.Google Scholar
Moseholm, E., & Fetters, M. D. (2017). Conceptual models to guide integration during analysis in convergent mixed methods studies. Methodological Innovations, 10(2), 1–11. https://doi.org/10.1177/2059799117703118CrossRefGoogle Scholar
Nzabonimpa, J. P. (2018). Quantitizing and qualitizing (im-)possibilities in mixed methods research. Methodological Innovations, 11(2), 1–16. https://doi.org/10.1177/2059799118789021CrossRefGoogle Scholar
Sandelowski, M., Voils, C. I., & Knafl, G. (2009). On quantitizing. Journal of Mixed Methods Research, 3(3), 208–222. https://doi.org/10.1177/1558689809334210CrossRefGoogle ScholarPubMed
Schoonenboom, J. (2018). Mixed methods in early childhood education. In Fleer, M. & van Oers, B. (eds.), International Handbook of Early Childhood Education (pp. 269–293). Springer. https://doi.org/10.1007/978-94-024-0927-7_11CrossRefGoogle Scholar
Schoonenboom, J. (2022). Developing the meta-inference in mixed methods research through successive integration of claims. In Hitchcock, J. H. & Onwuegbuzie, A. J. (eds.), The Routledge Handbook for Advancing Integration in Mixed Methods Research (pp. 55–70). Routledge. https://doi.org/10.4324/9780429432828-6CrossRefGoogle Scholar
Schoonenboom, J. (2023). Ten mixed methods integration strategies for obtaining a detailed understanding. In Tierney, R., Rizvi, F., Ercikan, K., & Smith, G. (eds.), International Encyclopedia of Education, 4th ed. Elsevier. https://doi.org/10.1016/B978-0-12-818630-5.11045-0Google Scholar
Schoonenboom, J., & Johnson, R. B. (2017). How to construct a mixed methods research design. Kölner Zeitschrift für Soziologie und Sozialpsychologie, 69(2), 107–131. https://doi.org/10.1007/s11577-017-0454-1CrossRefGoogle ScholarPubMed
Schoonenboom, J., & Johnson, R. B. (2021). The case comparison table: A joint display for constructing and sorting simple tables as mixed analysis. In Onwuegbuzie, A. J. & Johnson, R. B. (eds.), The Routledge Reviewer’s Guide to Mixed Methods Analysis (pp. 277–288). Routledge. https://doi.org/10.4324/9780203729434-24CrossRefGoogle Scholar
Schoonenboom, J., Johnson, R. B., & Froehlich, D. E. (2018). Combining multiple purposes of mixing within a mixed methods research design. International Journal of Multiple Research Approaches, 10(1), 271–282. https://doi.org/10.29034/ijmra.v10n1a17CrossRefGoogle Scholar
Tashakkori, A. M., Johnson, R. B., & Teddlie, C. B. (2021). Foundations of Mixed Methods Research: Integrating Quantitative and Qualitative Approaches in the Social and Behavioral Sciences, 2nd rev. ed. SAGE Publications.Google Scholar
Teddlie, C. B., & Tashakkori, A. (2009). Foundations of Mixed Methods Research: Integrating Quantitative and Qualitative Approaches in the Social and Behavioral Sciences. SAGE Publications.Google Scholar
Uprichard, E., & Dawney, L. (2019). Data diffraction: Challenging data integration in mixed methods research. Journal of Mixed Methods Research, 13(1), 19–32. https://doi.org/10.1177/1558689816674650CrossRefGoogle ScholarPubMed
Visser, L., Korthagen, F. A., & Schoonenboom, J. (2018). Differences in learning characteristics between students with high, average, and low levels of academic procrastination: Students’ views on factors influencing their learning. Frontiers in Psychology, 9(808). https://doi.org/10.3389/fpsyg.2018.00808CrossRefGoogle ScholarPubMed
Yin, R. K. (2006). Mixed methods research: Are the methods genuinely integrated or merely parallel? Research in the Schools, 13(1), 41–47.Google Scholar