About
Mixed methods refers to the combinations and comparisons of multiple data sources, data collection and analysis procedures, research methods, and/or inferences that occur at the end of a study.
The reality of many research projects is that they actually contain both qualitative and qualitative data, whether collected intentionally or not. See Dr. Trochim’s website http://www.socialresearchmethods.net/kb/datatype.htm for an explanation of the argument that these two types of data are actually interrelated. As he states,
“…qualitative and quantitative data are intimately related to each other. All quantitative data is based upon qualitative judgments; and all qualitative data can be described and manipulated numerically.”
Mixed Method Research Designs:
- Use both quantitative and qualitative data collection and analysis in an effort to capitalize on the above and combine the advantages of both types of data.
- They also allow a triangulation of evidence and methods that provide a stronger logical case for your conclusions.
| Sample Mixed Methods Designs |
| Type |
Description |
| Concurrent |
Parallel collection and analysis of both qualitative and quantitative data. |
| Sequential |
The collection of one type of data provides the basis for the collection of the other. |
| Qualitized or Quantitized |
Qualitative data are converted to quantitative data or vice versa. |
| Conversion |
After data have been converted, they are analyzed again. |
Further Readings:
Tashakkori, A. & Teddlie, C. (Eds.). (2003). Handbook of mixed methods in social and behavior research. Thousand Oaks, CA: Sage.
A collection of chapters demonstrating the range of definitions of mixed methods held by different authors and the types of research and analysis strategies.
Tashakkori, A., & Teddlie, C. (1998). Mixed Methodology: Combining the Qualitative and Quantitative Approaches (Applied Social Research Methods, No. 46). Thousand Oaks, CA: Sage.
A practical guide to mixed methods research including discussions of the underlying philosophical issues, a typology of methods and research issues, and sample studies
Greene, J. C., & Caracelli, V. J. (Eds.). (1997). Advances in Mixed-Method Evaluation: The Challenges and Benefits of Integrating Diverse Paradigms (New Directions for Evaluation, No. 74). San Francisco: Jossey-Bass.
This book addresses the philosophical issue of whether evaluative methods should be combined when they are believed to have different conflicting assumptions that underlie them. The attempt is to create a basis for mixed methods with a common “analytical space”.
