4 papers
Win-Ratio Regression for Prioritized Composite Outcomes in Observational Studies: Doubly Robust and Efficient Estimation with Future-Score Correction
Zhuochao Huang, Lucy Shao, Yi Guo +4
Prioritized pairwise outcomes are useful when clinical events follow a natural hierarchy, but censoring before pair resolution complicates estimation. We develop a win-ratio regres…
Multivariate incremental effects for continuous treatments: Studying the health effects of environmental mixtures
Zhuochao Huang, Kejin Dong, Tuo Lin +1
Evaluating the causal health effects of multivariate, continuous exposures, such as air pollution mixtures, is a critical public health challenge. A primary obstacle is the frequen…
Why Is the Double-Robust Estimator for Causal Inference Not Doubly Robust for Variance Estimation?
Hao Wu, Lucy Shao, Toni Gui +6
Doubly robust estimators (DRE) are widely used in causal inference because they yield consistent estimators of average causal effect when at least one of the nuisance models, the p…
Causal inference and racial bias in policing: New estimands and the importance of mobility data
Zhuochao Huang, Brenden Beck, Joseph Antonelli
Studying racial bias in policing is a critically important problem, but one that comes with a number of inherent difficulties due to the nature of the available data. In this manus…