collaborators

9 papers

stat.ME2026

A Causal Inference Approach for Evaluating Diagnostic Tests and AI-Enabled Medical Devices: From Effect Modification to Information-Augmented Decision-Making

Wenxin Zhang, Rachael Phillips, Mark van der Laan

Diagnostic medical tests and devices provide useful information for evaluating the potential benefits and risks of therapeutic treatments. However, unlike treatments, their impact…

stat.ME2026

Longitudinal Adaptive Experimental Design for Learning Multiple Target Estimands with Semiparametric Efficient Inference

Wenxin Zhang, Mark van der Laan

Adaptive designs are increasingly used in clinical trials and digital experiments to improve estimation efficiency by updating treatment randomization probabilities as data accumul…

stat.ME2026

The V-fold jackknife for semiparametric inference: variance estimation, confidence intervals, and simultaneous confidence bands

Yi Li, Ashkan Ertefaie, Mark van der Laan

For decades, the bootstrap has been a default tool for statistical inference because of its broad applicability and minimal analytic requirements. Although its validity is well und…

stat.ME2026

Targeted Learning on Variable Importance Measure for Heterogeneous Treatment Effect

Haodong Li, Alan E Hubbard, Oliver J Hines +3

Quantifying the heterogeneity of treatment effect is important for understanding how a commercial product or medical treatment affects different population subgroups. While much of…

stat.ME2025

Constructing Confidence Intervals for Infinite-Dimensional Functional Parameters by Highly Adaptive Lasso

Wenxin Zhang, Junming Shi, Alan Hubbard +1

Estimating the conditional mean function is a central task in statistical learning. In this paper, we consider estimation and inference for a nonparametric class of real-valued cad…

stat.ME2025

HAL-Based Plug-in Estimation with Pointwise Asymptotic Normality of the Causal Dose-Response Curve

Junming Shi, Wenxin Zhang, Alan E. Hubbard +1

Estimating and obtaining reliable inference for the marginally adjusted causal dose-response curve for continuous treatments without relying on parametric assumptions is a well-kno…