1 citations · 2 across the 5 of their papers we have counts for
5 papers
Priority-Standardized Net Benefit: A Stage-Normalized Estimand for Hierarchical Composite Endpoints
David McCoy, John Leopold, Shirley Galbiati +2
Hierarchical composite endpoints analyzed with win statistics are increasingly used when outcomes differ in clinical importance and hard events are too rare to support a single-com…
Data-Adaptive Identification of Effect Modifiers through Stochastic Shift Interventions and Cross-Validated Targeted Learning
David McCoy, Wenxin Zhang, Alan Hubbard +2
In epidemiology, identifying subpopulations that are particularly vulnerable to exposures and those who may benefit differently from exposure-reducing interventions is essential. F…
Unveiling Causal Mediation Pathways in High-Dimensional Mixed Exposures: A Data-Adaptive Target Parameter Strategy
David B. McCoy, Alan E. Hubbard, Mark van der Laan +1
Mediation analysis in causal inference typically concentrates on one binary exposure, using deterministic interventions to split the average treatment effect into direct and indire…
Semiparametric Discovery and Estimation of Interaction in Mixed Exposures using Stochastic Interventions
David B. McCoy, Alan E. Hubbard, Alejandro Schuler +1
This study introduces a nonparametric definition of interaction and provides an approach to both interaction discovery and efficient estimation of this parameter. Using stochastic…
Discovery of Critical Thresholds in Mixed Exposures and Estimation of Policy Intervention Effects using Targeted Learning
David McCoy, Alan Hubbard, Alejandro Schuler +1
Traditional regulations of chemical exposure tend to focus on single exposures, overlooking the potential amplified toxicity due to multiple concurrent exposures. We are interested…