AI Paper Atlas

Research map / Probabilistic and scientific modeling / Treatment effects

Counterfactual Randomization: Rescuing Experimental Studies from Obscured Confounding

AAAI 2019 · Probabilistic and scientific modeling › Treatment effects · approach: Latent-variable causal inference · 11 citations (OpenAlex)

Read the paperCheck your idea against 108,967 papers

AI-extracted summary. Written by AI from the paper's title only (no summary yet). Numbers and claims can be wrong or missing context, so check the paper before you cite or build on it.

Measured effects reported in the paper

What was changedWhereMeasuredEffect
cluster actors into intent equivalence classes (ablation)HI-RDC online agent · Confounded Physicians MABUCcumulative u-regret: 153.52 -> 68.13Helped
choose calibration set by heuristics instead of at random (ablation)HI-RDC-RCT agent · Confounded Physicians MABUCcumulative u-regret: 67.28 -> 46.78Helped
add HI-RCT calibration set (random selection) (ablation)HI-RDC-L agent · Confounded Physicians MABUCcumulative u-regret: 68.13 -> 67.28No clear effect
combine intents of both physicians instead of a single physician's intentRDC recommender · Confounded Physicians exampleexpected recovery rate: 72.5% -> 77.5%Helped

Closest papers by meaning

Writing a paper in this area? scime draft is a free LaTeX editor with AI included, real-time co-authors and a check of your references and venue rules before you submit. It also imports OpenAI Prism projects.

Open scime draft

Get the next scime Dispatch and a monthly field update

Free. We send a confirmation link first; every email has a one-click unsubscribe. Privacy