Causal Analysis with Structural Equation Models and Bayesian Networks
About the Presenter
Dr. Lionel Jouffe CEO, Bayesia S.A.S.
Abstract
Throughout the 2014 BayesiaLab User Conference program, participants have heard extensively about the theory of causal analysis with graphical models. This was the focus of Felix Elwert's 2-day course, September 19–20, and Judea Pearl's keynote on September 23.
In this presentation, we show how these theoretical causal concepts can be translated immediately for use in practical research with the BayesiaLab software platform. BayesiaLab offers a wide array of features that were specifically developed for causal analysis, such as Path Analysis, Likelihood Matching, Intervention, Total and Direct Effects.