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New Video Lecture: Causality for Policy Assessment and Impact Analysis
Presenters: Stefan Conrady and Dr. Lionel Jouffe
Recorded on November 18, 2014, at George Mason University Arlington Campus.
Runtime: 01:52:24
The objective of this presentation is to provide a practical framework for causal effect estimation with non-experimental data. We will present a range of methods, including Directed Acyclic Graphs and Bayesian networks, which can help distinguish causation from association when working with data from observational studies. The presentation revolves around a seemingly trivial example, Simpson’s Paradox, which turns out to be rather tricky to interpret in practice.
This talk is a "live" version of a recent tutorial, Causality for Policy Assessment and Impact Analysis - Directed Acyclic Graphs and Bayesian Networks for Causal Identification and Estimation. .... "
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