Causal Effects
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en  Theory and analysis of conditional and average causal effects at the European Congress of Methodology [EAM 2018]

Speakers: Prof. Dr. Rolf Steyer

Summer term 2018, Workshop, Language: English, Topic: Analysis of causal effects

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.

Contents

  • 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

This course was a pre-conference workshop in front of the VIII European Congress of Methodology [EAM 2018] at the University of Jena, Germany.



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Video of this workshop