Willy Brandt School of Public Policy, Universität Erfurt
Patrick A. Mello is Research and Teaching Associate at the Chair of European and Global Governance at the Bavarian School of Public Policy, Technical University of Munich.
His substantive research focuses on international security and foreign policy analysis, and his methodological research interests lie in comparative and case study approaches, with an emphasis on fuzzy-set QCA.
Patrick's work has appeared in journals such as the European Journal of International Relations, the Journal of International Relations and Development, and West European Politics.
His research focuses on regime transitions, autocratic regimes, the qualities of democracies, and the link between social and political inequalities. He also works in the field of comparative methodology, especially on set-theoretic methods.
Carsten Q. Schneider is Head of the Department of Political Science at Central European University, Budapest. His research focuses on regime transitions, the consolidation and qualities of democracy, and measuring political regimes. His book The Consolidation of Democracy in Europe and Latin America has been published with Routledge in 2009. His second field of interest consists in methodology, especially set-theoretic methods, with a focus on Qualitative Comparative Analysis (QCA). He has published in Sociological Methods and Research, European Journal of Political Research, Political Research Quarterly, Socio-Economic Review, and others. His book Set-Theoretic Methods for the Social Science, co-authored with Claudius Wagemann, has been published with Cambridge University Press in 2012.
Patrick A. Mello is a research associate and lecturer at the Chair of International Politics, Technische Universität Dresden (Germany). His substantive research focuses on matters of international relations theory, international security, and foreign policy analysis. His methodological research interests evolve around comparative and case study approaches, with an emphasis on fuzzy-set Qualitative Comparative Analysis. He has recently published in the European Journal of International Relations and the Journal of International Relations and Development. His book Democratic Participation in Armed Conflict: Military Involvement in Kosovo, Afghanistan and Iraq has been published with Palgrave Macmillan in 2014.
Students are not required to have any prior knowledge of QCA or the R software environment and its QCA package. However, they are strongly encouraged to familiarize themselves with the basic principles of the method in advance by reading the recommended literature as specified in the reading list. A previous introduction to the basic functions of R and RStudio will be useful to start working with the software from day 1.
This course introduces participants to set-theoretic methods and their application in the social sciences with an emphasis on Qualitative Comparative Analysis. The introductory course is complemented by an advanced course that is taught during the ECPR Winter School in Bamberg. The course starts out by familiarising students with the basic concepts of the underlying methodological perspective, among them the central notions of necessity and sufficiency, formal logic and Boolean algebra. From there, we move to the logic and analysis of truth tables and discuss the most important problems that emerge when this analytic tool is used for analysing social science data. All analytical issues will be introduced on crisp sets and later expanded to fuzzy sets. Right from the beginning, students will be exposed to performing set-theoretic analyses using the relevant R software packages. When discussing set-theoretic methods, in-class debates will further engage on broad, general comparative social research issues, such as case selection principles, concept formation, questions of data aggregation and the treatment of causally relevant notions of time. Real-life published applications are used throughout the course. Participants are encouraged to bring their own data for in-class exercises and assignments, if available. To get the most out of the course, participants would profit from some basic empirical-comparative training and an introduction to the R environment (e.g., Refresher Course), but these are no prerequisites in a strict sense.
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.