Dr Jason Seawright is an Associate Professor of Political Science at Northwestern University. He is the author of two books, Party-System Collapse: The Roots of Crisis in Peru and Venezuela (Stanford, 2012) and Multi-Method Social Science: Combining Qualitative and Quantitative Tools (Cambridge, 2016). He has also published in Political Analysis, Sociological Methods and Research, the American Journal of Political Science, Perspectives on Politics Comparative Political Studies, among other journals and edited volumes. His research interests include causal inference, mixed-methods research designs, political parties and party systems, populism, and political representation.
Course Content: The course will discuss mixed-method research in the sense of research designs that incorporate quantitative as well as case-study components. It will focus primarily on issues of causal inference, and the first sessions will review statistical theories of causation, and also discuss causal inference in regression and case studies. The course will then cover research designs in which qualitative components are used to test the assumptions of regression-based causal inference. Topics include looking for confounders, measurement error, mediation, and case selection. The course then turns to designs using more advanced statistical methods: matching, natural experiments, true laboratory experiments, and machine learning tools. Finally, the course considers designs in which a qualitative causal inference is improved using statistical design components.
Course Objectives: Participants should expect to develop an increased ability to notice and take advantage of aspects of the theories or hypotheses that they test which are open to consideration using multiple research designs. They will also possess a toolkit of statistical techniques and case-study ideas that facilitate successful multi-method research. These tools and abilities are particularly useful in planning and executing coherent large-scale research projects, such as book-length work in which multiple research components are intended to speak to a common underlying theory or question.
Course Prerequisites: Students should have carried out regression analysis using real social scientific data at least a few times. They should be able to read and interpret the standard regression tables routinely published in social science journals. They should also have read at least some instances of case-study research in the social sciences.
Representative Background Reading:
Lieberman, Evan S. 2005. Nested analysis as a mixed-method strategy for comparative research. American Political Science Review 99 (3): 435-52.
Required texts: Seawright, Jason. Multi-Method Social Science: Combining Qualitative and Quantitative Tools (Cambridge, 2016). ISBN: 978-1107483736. This text will be provided as part of the course material provided by the Summer School.