Vrije Universiteit Amsterdam
Political and Policy Research: Philosophy and Design
Type: Graduate methods course
Goal: This course is intended to introduce students to fundamental issues in the design of research in comparative political science and, therefore, to assist students in the development of their own research generally and more particularly in the preparation of their master dissertations. It focuses on the interplay of theory, hypotheses, empirical strategies, and data. The course is structured to deal with an interconnected set of issues facing researchers: the value of the comparative method in explaining political phenomena; the choice of substantively significant and tractable research topics; the development of concepts and their operationalisation; the choice of methods that match the research question; case selection and data collection; ethical issues in comparative political science.
Materials: Please contact me for the syllabus or course materials. For VU students, please refer to Canvas and Study Guide.
Workshop in Democracy, Power and Inequality
Type: Graduate course
Goal: This course aims to train students in doing political science and political economy themselves with a specific emphasis on democracy. This workshop surveys the literature on democracy to answer questions such as these: How is democracy conceptualised? What are the relevant distinctions among democracies? How can we measure democracy? What are the social, economic, cultural and political prerequisites of democracy? What effect does the political and economic performance have on the public support for democracy? Is democracy in decline today? These questions are approached by the selected literature both from the macro-perspective of institutions and context conditions as well as from the micro-perspective of the citizens and their understanding and evaluation of the way democracy works. At the same time, several of the selected texts deployed the methodological tools to approach these questions empirically.
Materials: Please contact me for the syllabus or course materials. For VU students, please refer to Canvas and Study Guide.
Applying Quantitative Methods in Political Science
Type: Graduate methods course
Goal: In this graduate course on applied quantitative methods, students will gain both theoretical knowledge and hands-on experience with quantitative research method. The course equips students with the tools to estimate empirically sound models that address substantive concerns in political science. While model estimation may be straightforward, the real challenge lies in developing models that yield meaningful insights into political phenomena. To achieve this, students will study the underlying principles of their chosen approach, develop research designs, and engage in data collection and analysis. Our focus will be on understanding how estimates are produced, what they signify, and determining which estimates can be trusted. The skills acquired in this course will also provide a solid foundation for students to apply in writing their MSc thesis.
Materials: Please contact me for the syllabus or course materials. For VU students, please refer to Canvas and Study Guide.
Quantitative Research and Methods in Political Science
Type: Undergraduate methods course
Goal: This course is intended for second-year undergraduate students with prior training in descriptive and inferential statistics. Topics covered include multiple linear regression, non-linear models, causality and experimental designs, as well as discussions on how inference and estimation should and should not be used in social science research.
Materials: Please contact me for the syllabus or course materials. For VU students, please refer to Canvas and Study Guide.
ECPR Methods School
Bayesian Modelling
Type: PhD methods course
Goal: This course aims at introducing the theoretical and applied principles of Bayesian statistics specifically geared toward students in social science. It will cover the differences between Bayesian and Frequentist approaches and the advantages of using the Bayesian approach for social scientists. Second, the course will cover the theoretical foundation of Bayesian statistics and introduce stochastic simulation methods for inference (Markov chain Monte Carlo). Third, it will focus on using Bayesian models in political science data analysis. The topics include linear models, logit/probit, poisson/negative binomial, hierarchical models, measurement models, as well as Bayesian model averaging. Examples are mainly drawn from political science, economics, and sociology.
Materials: Please contact me for the syllabus or course materials. For ECPR participants, please refer to Canvas and ECPR website.
Text as Data
Type: PhD methods course
Goal: This course covers several methods for systematically extracting and analysing quantitative information from text for social scientific purposes. First, starting with information extraction, it discusses web scrapping techniques and how to obtain and process text data. Descriptive analysis of texts and dictionary methods will also be covered, followed by supervised and unsupervised machine learning techniques, scaling, topic models and embeddings. The course lays a theoretical foundation for text-as-data approach but mainly adopts an applied perspective, by introducing students to modern quantitative text analysis techniques, with the ultimate goal of providing the skills necessary to apply the methods in their own research.
Materials: Please contact me for the syllabus or course materials. For ECPR participants, please refer to Canvas and ECPR website.
European University Institute (2019)
Bayesian Statistics for Political Science
Type: PhD & faculty methods course
Goal: This workshop aims at introducing the basic theoretical and applied principles of Bayesian statistics specifically geared toward researchers in political science. Despite the usefulness of the Bayesian approach, it is less taught among researchers of political science compared with the frequentist paradigm. The Bayesian framework is particularly useful for the type of data that political scientists encounter. It is a formal method for combining prior information with observed quantitative information; it offers a more general way to deal with issues of model identification, and it allows researchers to fit very realistic, sometimes complicated, models. Topics covered includes standard statistical models from a Bayesian perspective and advanced topics, such as models for multivariate outcomes and Bayesian change point analysis.
Materials: Please contact me for the syllabus or course materials.