Germany, Cologne

Research Designs and Causal Inference

online course
when 29 July 2020 - 31 July 2020
language English
duration 1 week
fee EUR 160

Social scientists are frequently interested in drawing causal inferences. Typical research interests refer to the analysis of the causes of social phenomena and the mechanisms constituting them. The extent to which an outcome of interest can be traced back to a specific cause-referred to as the internal validity-is highly dependent on how the empirical study is organized and conducted, i.e., on the underlying research design. For this reason, design decisions are crucial to the success of any causal analysis. Against this backdrop, the relations between research questions and different research designs are discussed, taking into consideration the respective strengths and weaknesses of the different designs for answering causal questions. We cover ex-post-facto, (quasi-)experimental and longitudinal designs. In the course of mechanistic thinking, we also introduce the principles of causal graphical models that have proven to be effective for causal effect identification.

Course leader

Prof. Dr. Stefanie Eifler is professor of Sociology and Empirical Social Research at the Catholic University of Eichstätt-Ingolstadt, Germany;
Dr. Heinz Leitgöb is research associate at the Catholic University of Eichstätt-Ingolstadt, Germany.

Target group

Participants will find the course useful if they:
- are considering to collect experimental or observational data to answer causal research questions and need advanced knowledge about potential research designs and their appropriate implementation;
- want to gain insight into the prerequisites of causal inference from a design perspective.

Prerequisites:
Participants should have graduate-level knowledge about
- main types of research and sampling designs,
- survey methodology,
- main techniques of cross-sectional and longitudinal data analysis.

Course aim

By the end of the course participants will:
- have obtained an extensive overview over various types of quantitative research designs;
- be familiar with the concept of causality from different perspectives:
- be able to select the appropriate research design to answer causal research questions.
The course does not cover how to investigate or model causal effects using statistical software!

Credits info

- Certificate of attendance issued upon completion.

Fee info

EUR 160: Student/PhD student rate.
EUR 240: Academic/non-profit rate.
The rates include the tuition fee and course materials.