148 citations · 196 across the 16 of their papers we have counts for
16 papers
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…
Prognostic Covariate Adjustment for Binary Outcomes Using Stratification
Alyssa M. Vanderbeek, Jessica L. Ross, David P. Miller +1
Covariate adjustment and methods of incorporating historical data in randomized clinical trials (RCTs) each provide opportunities to increase trial power. We unite these approaches…
Lassoed Tree Boosting
Alejandro Schuler, Yi Li, Mark van der Laan
Gradient boosting performs exceptionally in most prediction problems and scales well to large datasets. In this paper we prove that a ``lassoed'' gradient boosted tree algorithm wi…
Mixed models for repeated measures should include time-by-covariate interactions to assure power gains and robustness against dropout bias relative to complete-case ANCOVA
Alejandro Schuler
In randomized trials with continuous-valued outcomes the goal is often to estimate the difference in average outcomes between two treatment groups. However, the outcome in some tri…