All Stories

  1. Sufficient Causes: On Oxygen, Matches, and Fires
  2. On the Interpretation of do(x)do(x)
  3. The seven tools of causal inference, with reflections on machine learning
  4. Does Obesity Shorten Life? Or is it the Soda? On Non-manipulable Causes
  5. What is Gained from Past Learning
  6. Theoretical Impediments to Machine Learning With Seven Sparks from the Causal Revolution
  7. Physical and Metaphysical Counterfactuals: Evaluating Disjunctive Actions
  8. A Linear “Microscope” for Interventions and Counterfactuals
  9. Preface to the ACM TIST Special Issue on Causal Discovery and Inference
  10. The Sure-Thing Principle
  11. Lord’s Paradox Revisited – (Oh Lord! Kumbaya!)
  12. Detecting Latent Heterogeneity
  13. Comment on Ding and Miratrix: “To Adjust or Not to Adjust?”
  14. Conditioning on Post-treatment Variables
  15. Generalizing Experimental Findings
  16. TRYGVE HAAVELMO AND THE EMERGENCE OF CAUSAL CALCULUS
  17. The Mediation Formula: A Guide to the Assessment of Causal Pathways in Nonlinear Models