Oslo Summer School in Comparative Social Science Studies 2014

Mixed Methods: Integrating Qualitative and Quantitative Research

Lecturer: Prof. Dr. Udo Kelle,
Helmut-Schmidt-University Hamburg,
Germany

Main disciplines: Sociology, Political Science, Psychology, Research Methods

Dates: 28 July - 1 August 2014
Course Credits: 10 pts (ECTS)
Limitation: 25 participants


Objectives
Mixed methods – the integration of qualitative and quantitative methods in one research design – is an important and up to date topic in social research methodology. The course will give an overview about current debates regarding mixed methods and about the most important (agreed-upon and contested) issues in the field. Furthermore, course participants will develop competencies to develop and choose a mixed methods design and mixed methods strategy suited to answer specific research questions. For this purpose, students shall become familiar with the essential types of mixed methods designs and shall learn about reasons for using such designs and about criteria to assess the quality of designs and findings from mixed methods studies. During the course both problems of research practice and deeper reaching epistemological questions regarding the relation of qualitative and quantitative methods will be discussed. Since mixed methods designs are used to compensate for specific limitations of qualitative or quantitative (mono)methods special emphasis is laid on problems of qualitative and quantitative research – thereby we will explore problems of operationalization and measurement, problems of statistical inference, of generalizability and sampling, of (causal) explanation, theory testing and theory generation, both in qualitative and quantitative research. By drawing on examples from research practice it will be demonstrated how such problems of qualitative and quantitative methods can be detected, dealt with and overcome in a mixed methods design by drawing on the respective other tradition. Finally, it will be discussed how qualitative and quantitative findings from a mixed methods study can be meaningfully integrated and how convergent, contradictory and complementary findings can be dealt with.

A limited number of participants will have the opportunity to discuss own ideas and plans regarding a mixed methods design (e.g. for a PhD project) during the course – students interested in using this option are asked to send a short description of their project (not more than three pages) covering the following issues: 1) purpose(s) and research question(s) of the whole research project, 2) short description of the qualitative and quantitative part of the study (sampling, data collection and data analysis methods), 3) purposes for using different methods – which part of the research question(s) shall be answered with the help of the qualitative and quantitative part of the study?

To earn a course certificate together with 10 ECTS credits points for a PhD program a short essay (3.000 – 4.000 words) must be submitted within two months after the course.


Specific requirements
Since the focus of the course is not on qualitative and quantitative methods itself (although short summarizing overviews about essentials of qualitative and quantitative methodology and methods will be given) it is expected that course participants have at least basic knowledge about qualitative and quantitative research methods.


COURSE SCHEDULE

Lecture 1: Introduction and Overview– the qualitative-quantitative divide and mixed methods
The first lecture gives an introduction into the history of the “qualitative-quantitative divide” and into the origins and the development of the mixed methods movement. Contrary to what conventional wisdom holds it is often difficult to clearly define quantitative and qualitative research and to mark the differences between these methodological traditions - boundaries between the two approaches are often blurred and contested. In this lecture we will also clarify the terms “qualitative” and “quantitative” with respect to data types, data collection strategies, methods of analysis, underlying models of the research process and research purposes.

Readings:

  • Tashakkori, Abbas; Teddlie, Charles (1998): Mixed methodology: combining qualitative and quantitative approaches. Thousand Oaks, CA.: Sage. Chapter 1: Introduction to mixed methods and mixed model studies in the social and behavioural sciences. pp. 3 – 19.
  • Johnson, Burke; Gray, Robert (2010): A history of philosophical and theoretical issues for mixed methods research. In: Tashakkori, Abbas; Teddlie, Charles (eds.): Sage handbook of mixed methods in social and behavioral research. Thousand Oaks, CA.: Sage, pp. 69 – 94.
  • Lewis-Beck, Michael S.; Bryman, Alan E ; Liao, Tim Futing (2004): The SAGE Encyclopedia of Social Science Research Methods, Vol 2, pp 893 – 898.


Lecture 2: Integrating quality and quantity – paradigmatic vs. problem oriented approaches
The second lecture addresses arguments and legitimations regarding both monomethod and mixed methods research. The role of methodological paradigms in choosing and developing a research design will be discussed. Which research questions require a mixed methods designs? A problem oriented approach towards mixed methods will be presented: qualitative and quantitative methods can help to cope with typical methodological problems of qualitative and quantitative monomethod research.

Readings:

  • Hammersley, Martyn (1997): The relationship between qualitative and quantitative research: paradigm loyalty versus methodological eclecticism. In: Richardson, John T.E. (ed.): Handbook of qualitative research methods for psychology and the social sciences. Leicester: BPS books, pp. 159 – 174.
  • Johnson, R. Burke; Onwuegbuzie, Anthony J. (2004): Mixed Methods Research: A Research Paradigm Whose Time Has Come. In: Educational Researcher, 33, pp. 14 – 26.
  • Biesta, Gert (2004): Pragmatism and the philosophical foundations of mixed methods research. In: Tashakkori, Abbas; Teddlie, Charles (eds.): Sage handbook of mixed methods in social and behavioural research. Thousand Oaks, CA.: Sage, pp. 95 – 118.


Lecture 3: Types of mixed methods designs – an overview
We will discuss different possibilities to systematize mixed methods designs. The most important design types are presented and it will be shown which problems of qualitative and quantitative monomethod research can be treated with the help of these designs.

Readings:

  • Creswell, John W.; Plano Clark, Vicki L. (2011): Designing and Conducting Mixed Methods Research. Thousand Oaks: Sage. Chapter 3: Choosing a Mixed Methods Design, pp. 53 – 106.
  • Morse, Janice; Niehaus, Linda (2009): Mixed Method Design. Principles and Practice. Walnut Creek, CA.: Left Coast Press. Chapter 2, 3 and 4, pp. 23 – 54.


Lecture 4: Theory building, operationalization and measurement and mixed methods
In lecture 4 to 7 we will go into more detail regarding the functions of different designs. Lecture 4 discusses processes of theory building, operationalization and measurement and how they can be supported and improved with a mixed methods design. Thereby we will make extensive use of examples from research practice.

Readings:

  • Kelle, Udo (2006): Combining Qualitative and Quantitative Methods in Research Practice – Purposes and Advantages. In: Gürtler, Leo; Huber, Günter L. (ed.). Special Guest Issue on Mixed Methods. Qualitative Research in Psychology,Vol. 3 (4), pp. 293-311.
  • Kelle, Udo; Lüdemann, Christian (1998): Bridge Assumption in Rational Choice Theory: Methodological Problems and Possible Solutions. In: Blossfeld, Hans-Peter; Prein, Gerald (eds.): Rational Choice Theory and Large-Scale Data Analysis. Boulder, Co.: Westview Press. pp. 112-125.


Lecture 5: Statistical data analyses and mixed methods
In lecture 5 it will be shown how statistical analyses (or more precisely: the interpretation of statistical data) can be supported and substantiated by information obtained by qualitative data and methods. By drawing on empirical examples we will discuss strategies to deal with complex and incomprehensible statistical distributions and correlations in a mixed methods design.

Readings:

  • Kelle, Udo (2006): Combining Qualitative and Quantitative Methods in Research Practice – Purposes and Advantages. In: Gürtler, Leo; Huber, Günter L. (Hg.). Special Guest Issue on Mixed Methods. Qualitative Research in Psychology, 3 (4), pp. 293-311.
  • Goldthorpe, John H. (2001): Causation, Statistics, and Sociology. In: European Sociological Review, 17 (1), S. 1-20.


Lecture 6: Generalizability, transferability and sampling issues in mixed methods
Qualitative findings obtained in small N studies are often subject to questions regarding their range and scope. In this session we will discuss how the differing concepts of  generalizability and transferability in qualitative and quantitative research may relate to each other and we will show (by drawing on examples from research practices) how these concepts may be reconciled in a mixed methods design.

Readings:

  • Kelle, Udo (2006): Combining Qualitative and Quantitative Methods in Research Practice – Purposes and Advantages. In: Gürtler, Leo; Huber, Günter L. (Hg.). Special Guest Issue on Mixed Methods. Qualitative Research in Psychology,Vol. 3 (4), pp. 293-311.
  • Lieberson, Stanley (2000): Small N´s and big conclusions: an examination of the reasoning in comparative studies based on a small number of cases.  In: Gomm, Roger.; Hammersley, Martyn; Foster, Peter (eds.): Case Study Method. Key Issues, Key Texts. London: Sage. S. 208-222.
  • Onwuegbuzie, Anthony; Collins, Kathleen (2007): A Typology of Mixed Methods Sampling Designs in Social Science Research. In: The Qualitative Report, 12 (2), pp.281-316.
  • Gobo, Gianpetro (2008): Re-conceptualizing generalization: old issues in a new frame. In: Alasuutari, Pertti, Bickman, Leonard, Brannen, Julia (eds.): The Sage handbook of social research methods. London: Sage, pp. 193 – 227.


Lecture 7: Qualitative data analysis and mixed methods
Qualitative theory building – the development of theoretical categories from qualitative data – can be combined in a mixed methods design with quantitative data analysis. However, such an approach also carries the risk of confusing incompatible research logics. In this session we will present several methods of combining qualitative and quantitative data analyses through quantifying qualitative data and codes and discuss their threats of validity.

Readings:

  • Kelle, Udo; Seidel, John (1995): Different functions of coding in the analysis of textual data. In: Kelle, Udo (ed.): Computer-aided qualitative data analysis. Theory, methods and practice. London: Sage, pp. 52 – 61.
  • Kuckartz, Udo (1995): Case oriented quantification. In: Kelle, Udo (ed.): Computer-aided qualitative data analysis. Theory, methods and practice. London: Sage, pp. 158 – 166.

For further reading about qualitative category building combined with quantitative analyses:

  • Kuckartz, Udo (2014): Qualitative text analysis. A guide to methods, practice and using software. London: Sage.


Lecture 8: Planning a mixed methods project and assessing the design of mixed methods studies
In this session we will discuss practical applications of mixed methods designs (presented by course participants and from the literature). Different criteria to assess the usefulness of a given mixed methods design will be treated.

Reading:

  • Morse, Janice M. (2009): Mixed Method Design. Principles and Procedures.. Walnut Creek, CA.: Left Coast Press. Chapter 7 (“Planning a mixed methods project”, pp. 77 - 84)


Lecture 9: Finding evidence, interpreting results and drawing inferences in mixed methods research
Lecture 9 and 10 are about the interpretation and integration of findings in mixed methods research. In a first step (lecture 9) we will focus on different types of inference and reasoning (induction, deduction and abduction) relevant for qualitative and quantitative monomethod research and for mixed methods designs. The role of so-called “meta-inferences” (inferences which integrate qualitative and quantitative findings) will be clarified.

Readings:

  • Erzberger, Christian; Kelle, Udo (2003): Making Inferences in Mixed Methods: The Rules of Integration. In: Tashakkori, Abbas & Teddlie, Charles (Hg.). Handbook of mixed methods for the social and behavioural sciences. Thousand Oaks, CA: Sage, S. 457 – 490.
  • Reichertz, Jo (2004): Abduction, Deduction and Induction in Qualitative Research. In: Flick, Uwe (ed.): A companion to qualitative research, London: Sage, pp. 159 – 164.
  • Miller, Steven (2003): Impact of Mixed Methods and Design on Inference Quality. In: Tashakkori, Abbas; Teddlie Charles (eds.): Handbook of Mixed Methods in Social and Behavioral Research. Thousand Oaks: Sage. Pp. 423 – 455.
  • Tashakkori, Abbas; Teddlie, Charles (2008): Quality of inferences in mixed methods research: Calling for an integrative framework. In: Bergmann, Manfred Max (ed.): Advances in mixed methods research. London: Sage. Pp. 101 – 119.


Lecture 10: The integration of qualitative and quantitative results in mixed methods research
In this session we will discuss how convergent, divergent and complementary qualitative and quantitative findings in mixed methods studies can be dealt with. By drawing on examples from research practice it will be shown how the integration of findings may help researchers to corroborate, to reject or to modify theories or hypotheses and to detect and solve methodological problems.

Readings:

  • Erzberger, Christian; Kelle, Udo (2003): Making Inferences in Mixed Methods: The Rules of Integration. In: Tashakkori, Abbas & Teddlie, Charles (Hg.). Handbook of mixed methods for the social and behavioural sciences. Thousand Oaks, CA: Sage, S. 457 – 490.


Complete reading list

  • Biesta, Gert (2004): Pragmatism and the philosophical foundations of mixed methods research. In: Tashakkori, Abbas; Teddlie, Charles (eds.): Sage handbook of mixed methods in social and behavioural research. Thousand Oaks, CA.: Sage, pp. 95 – 118. (23)
  • Creswell, John (2010): Mapping the developing landscape of mixed methods research. In: Tashakkori, Abbas; Teddlie, Charles (eds.): Sage handbook of mixed methods in social and behavioural research. Thousand Oaks, CA.: Sage, pp. 45 – 68. (23)
  • Creswell, John W.; Plano Clark, Vicki L. (2011): Designing and Conducting Mixed Methods Research. Thousand Oaks: Sage. Chapter 1 – 9 (287)
  • Erzberger, Christian; Kelle, Udo (2003): Making Inferences in Mixed Methods: The Rules of Integration. In: Tashakkori, Abbas & Teddlie, Charles (Hg.). Handbook of mixed methods for the social and behavioural sciences. Thousand Oaks, CA: Sage, S. 457 – 490 (33)
  • Reichertz, Jo (2004): Abduction, Deduction and Induction in Qualitative Research. In: Flick, Uwe (ed.): A companion to qualitative research, London: Sage, pp. 159 – 164. (5)
  • Gobo, Gianpetro (2008): Re-conceptualizing generalization: old issues in a new frame. In: Alasuutari, Pertti, Bickman, Leonard, Brannen, Julia (eds.): The Sage handbook of social research methods. London: Sage, pp. 193 – 227. (34)
  • Goldthorpe, John H. (2001): Causation, Statistics, and Sociology. In: European Sociological Review, 17 (1), S. 1-20. (19)
  • Hammersley, Martyn (1997): The relationship between qualitative and quantitative research: paradigm loyalty versus methodological eclecticism. In: Richardson, John T.E. (ed.): Handbook of qualitative research methods for psychology and the social sciences. Leicester: BPS books, pp. 159 – 174. (15)
  • Johnson, R. Burke; Onwuegbuzie, Anthony J. (2004): Mixed Methods Research: A Research Paradigm Whose Time Has Come. In: Educational Researcher, 33, pp. 14 – 26. (12)
  • Johnson, Burke; Gray, Robert (2010): A history of philosophical and theoretical issues for mixed methods research. In: Tashakkori, Abbas; Teddlie, Charles (eds.): Sage handbook of mixed methods in social and behavioral research. Thousand Oaks, CA.: Sage, Pp. 69 – 94. (25)
  • Kelle, Udo (2006): Combining Qualitative and Quantitative Methods in Research Practice – Purposes and Advantages. In: Gürtler, Leo; Huber, Günter L. (ed.). Special Guest Issue on Mixed Methods. Qualitative Research in Psychology,Vol. 3 (4), pp. 293-311 (18)
  • Kelle, Udo; Lüdemann, Christian (1998): Bridge Assumption in Rational Choice Theory: Methodological Problems and Possible Solutions. In: Blossfeld, Hans-Peter; Prein, Gerald (eds.): Rational Choice Theory and Large-Scale Data Analysis. Boulder, Co.: Westview Press. pp. 112-125. (13)
  • Kelle, Udo; Seidel, John (1995): Different functions of coding in the analysis of textual data. In: Kelle, Udo (ed.): Computer-aided qualitative data analysis. Theory, methods and practice. London: Sage, pp. 52 – 61. (9)
  • Kuckartz, Udo (1995): Case oriented quantification. In: Kelle, Udo (ed.): Computer-aided qualitative data analysis. Theory, methods and practice. London: Sage, pp. 158 – 166. (8)
  • Lewis-Beck, Michael S.; Bryman, Alan E ; Liao, Tim Futing (2004): The SAGE Encyclopedia of Social Science Research Methods, Vol 2, pp 893 – 898. (5)
  • Lieberson, Stanley (2000): Small N´s and big conclusions: an examination of the reasoning in comparative studies based on a small number of cases.  In: Gomm, Roger.; Hammersley, Martyn; Foster, Peter (eds.): Case Study Method. Key Issues, Key Texts. London: Sage. S. 208-222. (14)
  • Miller, Steven (2003): Impact of Mixed Methods and Design on Inference Quality. In: Tashakkori, Abbas; Teddlie Charles (eds.): Handbook of Mixed Methods in Social and Behavioral Research. Thousand Oaks: Sage. Pp. 423 – 455. (32)
  • Morse, Janice M.; Niehaus, Linda (2009): Mixed Method Design. Principles and Procedures. Walnut Creek, CA. (149)
  • Onwuegbuzie, Anthony; Collins, Kathleen (2007): A Typology of Mixed Methods Sampling Designs in Social Science Research. In: The Qualitative Report, 12 (2), pp.281-316 (35)
  • Reichertz, Jo (2004): Abduction, Deduction and Induction in Qualitative Research. In: Flick, Uwe (ed.): A companion to qualitative research, London: Sage, pp. 159 – 164. (5)
  • Tashakkori, Abbas; Teddlie, Charles (1998): Mixed methodology: combining qualitative and quantitative approaches. Thousand Oaks, CA.: Sage. Chapter 1: Introduction to mixed methods and mixed model studies in the social and behavioural sciences. pp. 3 – 19. (16 pages)
  • Tashakkori, Abbas; Teddlie, Charles (2008): Quality of inferences in mixed methods research: Calling for an integrative framework. In: Bergmann, Manfred Max (ed.): Advances in mixed methods research. London: Sage. Pp. 101 – 119. (18)


Recommendations for additional reading
There is a variety of voluminous sources about mixed methods. The current edition of the “Sage handbook of mixed methods in social & behavioral sciences” (edited by Abbas Tashakkori and Charles Teddlie, 2010) contains 31 articles about different aspects of mixed methods and gives a good and overview about the whole field. Vicki Plano-Clark and John Creswell published a collection of 23 important classical papers about mixed methods written between 1979 and 2007 (“The mixed methods reader, 2008, Thousand Oaks: Sage.)

A further good course book is:

  • Greene, Jennifer C. (2007): Mixed methods in social inquiry. San Francisco, CA.: Jossey Bass.

A comprehensive course book about the combination of qualitative data analysis with quantitative methods is provided by

  • Kuckartz, Udo (2014): Qualitative text analysis. A guide to methods, practice and using software. London: Sage.

 

The lecturer
Dr. Udo Kelle is Professor for Social Research Methods and Statistics at the Faculty for Humanities and Social Sciences at the Helmut-Schmidt-University in Hamburg. He holds degrees in psychology (Dipl.-Psych.) and sociology (Dr. phil and venia). He has taught research methods and social statistics on the undergraduate, graduate and postgraduate level at various universities in Germany and abroad. He is an experienced methodological supervisor for empirical doctoral dissertations and research projects. He has extensively worked and published about social research methods, with a focus on methods for the empirically grounded construction of typologies, on theory building and on the integration of qualitative and quantitative research. His most current research is about problems of research fieldwork in different organisations (care homes, schools, universities, armed forces) and social research as a specific type of social interaction.

Selected publications: The combination of qualitative and quantitative research methods in mathematics education – A “mixed-methods” study on the development of the professional knowledge of teachers. In: Bikner-Asbahs, A.; Knipping, C.; Presmeg, N. (Eds.): Doing Qualitative Research - Methodology and Methods in Mathematics Education. New York: Springer, 2014 forthcoming; Theorization from Data. In: Flick, Uwe (ed.): The Sage Handbook of Qualitative Data Analysis. London: Sage, 2013 forthcoming; Qualitative Research on Prejudice. Special issue of the „International Journal on Conflict and Violence“ (with F. Knappertsbusch and B. Milbradt), 2013; Vom Einzelfall zum Typus. Fallvergleich und Fallkontrastierung in der qualitativen Sozialforschung. Wiesbaden: VS (with S. Kluge) 2010; The Development of Categories – Different Approaches in Grounded Theory. In: Bryant, Anthony; Charmaz, Kathy (Hg.): Grounded Theory. London: Sage. p. 191 – 213, 2007


Back to main page

Tags: Sociology, Summer School, PhD, Research Methods, Mixed Methods, Psychology, Political Science
Published Dec. 10, 2013 2:03 PM - Last modified Sep. 12, 2017 2:16 PM