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Causal Effects EAM Fachgruppe Methoden und Evaluation (DGPs)

Workshops: Course information

en  Theory and analysis of conditional and average causal effects

Speakers: Prof. Dr. Rolf Steyer

Winter term 2017/2018, Workshop, Language: English, Topic: Analysis of causal effects

Course description

This short course is an introduction to the stochastic theory of causality, which is a generalization of the theory of causal effects in the tradition of J. Neyman and D. B. Rubin. In the course I will present the stochastic theory of causal effects and show how to use EffectLiteR for the analysis of conditional and average total effects.


  • Motivation: Simpson's paradox, non-orthogonal ANOVA
  • The scope of the theory: random experiments
  • The mathematical structure of causal models: causality space
  • True outcome variables, average and conditional causal effects
  • Prima facie effects
  • Sufficient conditions for unbiasedness
  • The role of randomization and other design techniques and strategies of data analysis
  • Estimating and testing average and conditional total effects via structural equation modeling (Applications using EffectLiteR) in some empirical examples

Course venue

Institute for Psychology, Berlin, Germany


If you are interested in this course, please send an E-Mail to christian.gische [ at ] hu-berlin.de .