Short Course C: Research Designs and Causal Inference

Lecturers: Prof. Dr. Stefanie Eifler, Dr. Heinz Leitgöb

Date: 2-3 August 2018
Time: 09:00-13:00, 14:00-16:00

Short Course Description:

Social scientists are frequently interested in the analysis of change and its causes. For this reason, 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 any causal analysis. 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.

Course 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

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. 

Course and Learning Objectives:

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!

Organizational Structure of the Course:

Both days will consist of three teaching blocks, each one and a half hours long. The rest of the time will be dedicated to assignments and individual consultations. More information about the topics covered in each of the teaching blocks is provided in the detailed description below. The instructors will give joint lectures supported by slides. Course participants are highly encouraged to engage actively and to contribute to the lectures in order to establish lively discussions. Course participants who want to profit from discussions of their own scientific work are asked to submit a one-page summary of their current or planned research to Stefanie Eifler and Heinz Leitgöb by July 15th.

Each day after the teaching blocks the course participants will have the opportunity for individual consultation.

Software and Hardware Requirements:

None.