AIWS University

Graphical Models and Instrumental Variables

At the request of readers, we re-post below a previous comment from Bryant and Elias (2014) concerning the use of graphical models for determining whether a variable is a valid IV. Dear Conrad,Following your exchange with Judea, we would like to present...

CAUSAL INFERENCE SUMMER SHORT COURSE AT HARVARD

We are informed of the following short course  at Harvard. Readers of this blog will probably wonder what this Harvard-specific jargon is all about, and whether it has a straightforward translation into Structural Causal Models. It has! And one of...

On Imbens’s Comparison of Two Approaches to Empirical Economics

Many readers have asked for my reaction to Guido Imbens’s recent paper, titled, “Potential Outcome and Directed Acyclic Graph Approaches to Causality: Relevance for Empirical Practice in Economics,” arXiv.19071v1 [stat.ME] 16 Jul 2019. The note...

Generalizing Experimental Results by Leveraging Knowledge of Mechanisms

In a recent post (and papers), Anders Huitfeldt and co-authors have discussed ways of achieving external validity in the presence of “effect heterogeneity.” These results are not immediately inferable using a standard (non-parametric) selection...

Fréchet Inequalities – Visualization, Applications, and History

Scott Mueller and Judea Pearl This post introduces readers to Fréchet inequalities using modern visualization techniques and discusses their applications and their fascinating history. Table of Contents Introduction Plots Examples Example 1 Example...

Which Patients are in Greater Need: A counterfactual analysis with reflections on COVID-19

Scott Mueller and Judea Pearl With COVID-19 among us, our thoughts naturally lead to people in greatest need of treatment (or test) and the scarcity of hospital beds and equipment necessary to treat those people. What does “in greatest need” mean?...

Artificial Intelligence and COVID-19

This past week, the Stanford Institute for Human-Centered Artificial Intelligence (HAI) has organized a virtual conference on AI and COVID-19, a video of which is now available. Being unable to attend the conference, I have asked the organizers to share...

Causal, Casual, and Curious (2013-2020): A collage in the art of causal reasoning

Journal of Causal Inference by Judea Pearl Introduction This collection of 14 short articles represents adventurous ideas and semi-heretical thoughts that emerged when, in 2013, I was given the opportunity to edit a fun section of the Journal of Causal...

Introduction for the Section “Modern Causal Inference” on AIWS.net

In “The Book of Why: The New Science of Cause and Effect”, Professor Judea Pearl, UCLA, wrote: “The ideal technology that causal inference strives to emulate is in our own mind. All because we asked a simple question: “Why?” Causal...