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Monday 17 – Friday 21 February 2019, 09:00–12:30
15 hours over five days
This course deals with mixed-methods / multimethod research (MMR) in the social sciences. To accommodate participants’ projects, it aims to reflect the diversity of MMR studies in the discipline.
We will discuss the broader understanding of combining qualitative and quantitative methods and the more focused approach, linking case studies and process tracing to a large-n method such as Qualitative Comparative Analysis (QCA) or regression analysis. The relative emphasis we put on specific variants of MMR designs will be adapted to the methods participants are applying in their own research.
The goal of the course is to understand the different varieties in which MMR can be done. We discuss the unique advantages and methodological and practical challenges confronted in implementing multi-method designs.
Topics include concepts in the qualitative and quantitative analysis, case selection for qualitative research, and the compatibility of theoretical expectations and inferences on causal effects and causal mechanisms. Method-centred discussions are illustrated with examples from different fields of political science.
By the end of the course, you will able to realise your own mixed-methods study in a systematic manner, and to critically evaluate published MMR studies.
Tasks for ECTS Credits
2 credits (pass/fail grade) Attend 90% of course hours, participate fully in in-class activities, and carry out the necessary reading and/or other work prior to, and after, classes.
3 credits (to be graded) As above, plus submit a short daily assignment on days 1, 2, 3 and 4. The first two assignments are based on your own projects. If you are not working on an MMR project, an equivalent exercise will be assigned. The last two assignments are about general methodological issues and published empirical research.
4 credits (to be graded) As above, plus, after the course, submit a 10–15 page description of your mixed-methods research design as it stands. If a you are not working on an MMR project, an equivalent exercise will be assigned.
Ingo Rohlfing is Professor of Methods of Empirical Social Research at the University of Passau
He researches social science methods with a focus on qualitative methods (case studies and process tracing), Qualitative Comparative Analysis and multimethod research.
Ingo is author of Case Studies and Causal Inference (Palgrave Macmillan) and he has published articles in Comparative Political Studies, Sociological Methods & Research and Political Analysis.
Mixed-method research is an enduring topic in the social sciences (e.g., Creswell and Piano 2011), but multi-method research (MMR) more narrowly defined, also known as nested analysis, is a relatively new topic.
After longstanding antagonistic discussions about the pros and cons of qualitative and quantitative methods, we now find a growing consensus that each method has its distinct advantages and that they work best in combination with each other.
This course builds on the debate about mixed-methods and multimethod research, and focuses on their unique advantages and challenges for empirical researchers seeking to combine two or more methods.
Day 1
Laying foundations for the rest of the course, we learn about different conceptions of causation and how they can be integrated in a single mixed-methods analysis. We introduce different varieties and dimensions of mixed-methods research such as the timing of the methods’ applications and their relative importance in the context of the broader design.
Day 2
We begin with a reflection on concepts and concept formation in MMR as the cornerstone of all empirical research. This session is based on two interrelated claims one finds in the methods literature. First, it is argued that concepts are thin in quantitative and thick in qualitative research. Second, it is claimed that this discrepancy creates problems of conceptual stretching, undermining causal analysis. We question whether these assertions are warranted and, to the extent that they are accurate, how concept formation can be improved.
Day 3
All about case selection. Depending on the mixed-methods design, case selection challenges can be diverse, ranging from the recruitment of participants for focus groups to the residual-based choice of countries after a macro-comparative regression. We will discuss the current state of debate on case selection in nested analysis (regression or QCA with follow-up process tracing) and reflect on additional case selection strategies pertinent to participants’ designs.
Day 4
We turn to the question of generalisation. Generalisation is considered in parts of the mixed-methods literature and ignored in others. The main focus lies on the generalisation of inferences generated in the qualitative analysis. According to a common line of reasoning, generalisation of qualitative conclusions is only possible under conditions that are difficult, if not impossible, to reconcile with the quantitative part. We will discuss generalisation strategies for different variants of mixed-method designs.
Day 5
Wrap-up session. We take a closer look at a published empirical study with regard to the topics of days 1–4, with specific focus on what can be called causal consistency or causal coherence. This means that one’s theoretical expectations regarding the large-n results and process tracing insights should fit with each other. Similarly, the conclusions that one derives from quantitative and qualitative analyses should be coherent. For example, a lack of fit occurs when process tracing leads to the conclusion that multiple factors work in conjunction, while the regression analysis models the effect of covariates as independent from each other. We discuss several sources and manifestations of inconsistency and strategies for achieving coherence over the course of the analysis.
THIS IS THE WINTER SCHOOL 2019 OUTLINE
In-depth discussion of participants’ research projects is central to this course. You should be at an advanced stage of a piece of mixed-methods research, so you can present and discuss your study in class.
The course does not teach the basics of regression analysis, QCA, case studies, process tracing, or any other method one might use in multi-method research. You should know them already, because this course focuses on how to combine these methods.
Sufficient knowledge of the methods you aim to use is essential for understanding the principles of multi-method research.
Day | Topic | Details |
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Day 1 | Introduction to mixed-methods research |
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Day 2 | Concepts and concept formation |
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Day 3 | Case selection |
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Day 4 | Generalization |
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Day 5 | Wrap-up session and lessons learned |
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Day | Readings |
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Day 1 |
COMPULSORY Seawright, Jason (2016) Johnson, R. Burke, Federica Russo and Judith Schoonenboom (2017) VOLUNTARY Lieberman, Evan S. (2005) Creswell, John W. and Vicki L. Plano Clark (2011) Small, Mario Luis (2011) Ahmed, Amel and Rudra Sil (2012) Beach, Derek and Ingo Rohlfing (2018) |
Day 2 |
COMPULSORY Coppedge, Michael (1999) Ahram, Ariel I. (2013) VOLUNTARY Sartori, Giovanni (1970) Collier, David and James E. Mahon (1993) Welch, Catherine, Maria Rumyantseva and Lisa Jane Hewerdine (2016) |
Day 3 |
COMPULSORY Lieberman, Evan S. (2005) Lange, Matthew (2009) Weller, Nicholas and Jeb Barnes (2016) VOLUNTARY Seawright, Jason and John Gerring (2008) Sharp, Julia L., Catherine Mobley, Cathy Hammond, Cairen Withington, Sam Drew, Sam Stringfield and Natalie Stipanovic (2012) Rohlfing, Ingo and Peter Starke (2013) Schneider, Carsten Q. and Ingo Rohlfing (2013) Gerring, John and Lee Cojocaru (2016) |
Day 4 |
COMPULSORY Kühn, David and Ingo Rohlfing (2016) Goertz, Gary (2017) VOLUNTARY Lieberson, Stanley (1991) Onwuegbuzie, AnthonyJ and NancyL Leech (2010) Spillman, Lyn (2014) |
Day 5 |
COMPULSORY Lange, Matthew (2009) As a wrap-up, we will discuss one multi-method study in detail: the intro, theory, quantitative analysis and one in-depth case study. We will discuss ahead of the Winter School who will read which of the case study chapters. |
A useful introduction to mixed-methods research in a broader sense:
Creswell, John W. and Vicki L. Plano Clark (2011)
Designing and Conducting Mixed Methods Research
Los Angeles: SAGE Publications: chap. 2, 3
A good, focused discussion of multimethod research:
Seawright, Jason (2016)
Multi-Method Social Science: Combining Qualitative and Quantitative Tools
Cambridge: Cambridge University Press
Summer School
Multivariate regression
QCA
Case study research
Process tracing
Intro to mixed-methods
Winter School
Process tracing (basic)
Winter School
QCA
Different advanced statistics courses