Advanced Multi-Method Research

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.

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.

Each course includes pre-course assignments, including readings and pre-recorded videos, as well as daily live lectures totalling at least three hours. The instructor will conduct live Q&A sessions and offer designated office hours for one-to-one consultations.

Please check your course format before registering.

Online courses

Live classes will be held daily for three hours on a video meeting platform, allowing you to interact with both the instructor and other participants in real-time. To avoid online fatigue, the course employs a pedagogy that includes small-group work, short and focused tasks, as well as troubleshooting exercises that utilise a variety of online applications to facilitate collaboration and engagement with the course content.

In-person courses

In-person courses will consist of daily three-hour classroom sessions, featuring a range of interactive in-class activities including short lectures, peer feedback, group exercises, and presentations.

Disclaimer

This course description may be subject to subsequent adaptations (e.g. taking into account new developments in the field, participant demands, group size, etc.). Registered participants will be informed at the time of change.

By registering for this course, you confirm that you possess the knowledge required to follow it. The instructor will not teach these prerequisite items. If in doubt, please contact us before registering.