Scientific Coordination
Dr.
Sebastian E. Wenz
Tel: +49 221 47694-159
Sebastian E. Wenz
Tel: +49 221 47694-159
Administrative Coordination
Angelika Ruf
Tel: +49 221 47694-162
Tel: +49 221 47694-162
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Short Course A: Using Directed Acyclic Graphs for Causal & Statistical Inference
About
Location:
Online via Zoom
Online via Zoom
General Topics:
Course Level:
Format:
Software used:
Duration:
Language:
Fees:
Students: 200 €
Academics: 300 €
Commercial: 600 €
Keywords:
Additional links
Lecturer(s): Dr. Julian Schuessler
Course description
This online short course uses causal graphs (or “directed acyclic graphs”, DAGs) as a remarkably simple, yet general and powerful framework to describe and discuss a large set of problems that empirical social scientists need to tackle. Is my question of interest descriptive or causal? How can I communicate my assumptions effectively to others, and can I test them? How can I tell correlation from causation? How do I choose control variables for my regression models? After discussing how DAGs can be used to answer these foundational questions, the course also covers basics of causal interaction and effect heterogeneity, causal mediation, nonresponse/selection bias (and adjustments for it) and, if time permits, instrumental variables and panel data analysis from a DAG perspective.
The detailed syllabus with course times and literature will be available soon.
Target group
Participants will find the course useful if:
Learning objectives
By the end of the course participants will:
Organizational Structure of the Course
This short course throughout will change between short lecture-style inputs and individual or small-group hands-on exercises supervised by the lecturer and a teaching assistant (4hrs/day). Participants are encouraged to bring their own research ideas to develop them further using the material from the class. The lecturer will also be available for individual consultation in the afternoons.
Prerequisites
Participants should be willing to learn and use formal reasoning and must have at least Bachelor-level knowledge of statistics. Basic knowledge of R is helpful.
Software and Hardware Requirements
We will briefly discuss some elements of the R packages “dagitty”, “sensemakr”, “mediation”, “AER”, “estimatr”, “PanelMatch”. Most of the course will not depend on using R. For those who have never used R, here are installation instructions and a short introductory video: