Multilevel data structures are all over the social sciences: observations within municipalities, cantons, districts, or countries. Students within schools. Patients within hospitals. Multiple observations taken from the same person or any other unit of analysis. In quantitative studies, relevant predictors appear on all these levels of analysis. But how do we deal with them?

The course is designed to provide scholars with a basic understanding of multilevel (a.k.a. Hierar-chical linear or mixed effects) regression models designed to solve these problems. Special attention is given to the translation of theoretical expectations into statistical models, the interpretation of results in multilevel analyses, and the general use and misuse of multilevel models in the social sciences. While the course is predominantly designed to give you the knowledge of multilevel regres-sion modeling, it does also arm you with the basic tools to run multilevel models in R. (I also have Stata code for most of the models presented thanks to a former teaching assistant, but I am not a Stata user so there you are on your own.) Applications will include models with continuous and limited dependent variables in hierarchical, longitudinal, and cross-classified nesting situations and, if time allows, multilevel structural equation models. The goal of the course is to offer a basic intro-duction and the foundation for participants to start using and critically assessing multilevel models and also have the ability to independently discover and master advanced multilevel statistical topics. Upon completion, the participants will have a basic conceptual understanding of multilevel modeling and its statistical foundations. Participants will be able to critically assess the appropriateness of such techniques in their own and other people’s research and conduct multilevel modeling them-selves to the highest academic standards.

+ More Information(159.3 KB)

Course outline

This five-day course provides a hands-on introduction to case-based designs, enabling participants to use them in their own research. The course is designed to be relevant for participants from a range of different social science disciplines. A constant theme throughout the course will be on debating the strengths and limitations of different case-based methods, illustrating the types and scopes of inferences that are possible, and how they differ from what variance-based methods enable.

+ More Information(307.3 KB)

Timetable

Monday
will first introduce the foundations of case-based designs in terms of taking cases as the analytical point of departure. The course will distinguish between comparative and within-case designs.

Tuesday
deals with concepts and theories in case-based designs. After discussing how concept structure is dealt with, we will explore different types of theoretical relationships that are assessed using case-based designs, including necessary and sufficiency, as well as theories of causal processes (aka mechanisms).

Wednesday
unpacks different tools for comparative analysis, including more simple comparisons using tools such as Mill’s methods, and most-similar and most-different systems designs. Participants will also be introduced to the basics of Qualitative Comparative Analysis (QCA).

Thursday
deals with within-case analysis, focusing in particular on process-tracing methods. Using a published example, we will discuss how theories about causal processes can be developed and what elements they should include, as well as how process tracing works with empirical evidence.

Friday
presents the most central case selection principles, including typicality, deviant cases, and theoretical likelihood (most- and least-likely cases). We will then discuss how cross-case comparisons and within-case tracing can be combined in practice.

Instructor

Derek Beach is a professor of Political Science at Aarhus University, Denmark, where he does research on research methodology and European integration. He has authored articles, chapters, and books on research methodology, policy evaluation, international negotiations, referendums, and European integration, and co-authored the book Process-tracing Methods: Foundations and Guidelines (2019, 2nd edition, University of Michigan Press). He has taught case study methods at numerous workshops and ph.d. level courses throughout the world, and conducted evaluations at the national and international level. He was an academic fellow at the World Bank’s Independent Evaluation Group in spring 2022 and is an academic coordinator of the Methods Excellence Network (MethodsNet).

Date & Time:07.04-11.04.2024,, 9.30 a.m.-1.00 p.m. 

Place: FG1/FMA, Feldkirchenstra?e 21, 96052 Bamberg

Registrationn (by Tuesday, 04.03.2025 at the latest): courses.bagss(at)uni-bamberg.de