3 papers
cs.AI2026
Ice Cream Doesn't Cause Drowning: Benchmarking LLMs Against Statistical Pitfalls in Causal Inference
Jin Du, Li Chen, Xun Xian +6
Reliable causal inference is essential for making decisions in high-stakes areas like medicine, economics, and public policy. However, it remains unclear whether large language mod…
stat.ME2025
Doubly robust pointwise confidence intervals for a monotonic continuous treatment effect curve
Charles R. Doss
We study nonparametric inference for the causal dose-response (or treatment effect) curve when the treatment variable is continuous rather than binary or discrete. We do this by de…
stat.ME2024
Doubly robust estimation and inference for a log-concave counterfactual density
Daeyoung Ham, Ted Westling, Charles R. Doss
We consider the problem of causal inference based on observational data (or the related missing data problem) with a binary or discrete treatment variable. In that context, we stud…