5 August 2016
Research Designs and Causal Inference
Social scientists are frequently interested in the analysis of change – e.g. attitude change or behavior change. Typical research interests refer not only to the observation of change but first and foremost to the analysis of its causes – the question why change occurs is at the core of many empirical studies in social science research. The extent to what change can be traced back to a specific cause unambiguously – the so-called internal validity – depends on the order and the course of the empirical study, in other words, the research designs. For this reason, decisions concerning the research design are crucial to the success of causal analyses. Against the background of these considerations, different ways to classify research designs are introduced, and the relations between research questions and designs are introduced and discussed with regard to the strengths and weaknesses of different kinds of research designs.
You can find the full syllabus of the course with complete information on the topics, literature, and day-to-day schedule on https://training.gesis.org.
Prof. Dr. Stefanie Eiflerr is professor of Sociology and Empirical Social Research at the Catholic University of Eichstätt-Ingolstadt, Germany;
Heinz Leitgöb is research associate at the Catholic University of Eichstätt-Ingolstadt, Germany.
Participants will find the course useful if:
- they are considering collecting experimental or observational data in order to answer explanatory/causal research questions and need more background knowledge about the various potential research designs and their appropriate implementation;
- they want to gain insight into the prerequisites of causal inference from a research design perspective.
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 is not aimed at covering how to statistically model causal effects on the basis of experimental or observational data.
Participants should have basic knowledge about:
- the main types of research designs;
- the difference between correlation and causality.
EUR 100: Student/PhD student rate.
EUR 140: Academic/non-profit rate.
The rates include the tuition fee, course materials, access to library and IT facilities and coffee/tea.