134 citations · 468 across the 85 of their papers we have counts for
10 papers · 1 filter
Assessing treatment effects in observational data with missing confounders: A comparative study of practical doubly-robust and traditional missing data methods
Brian D. Williamson, Chloe Krakauer, Eric Johnson +13
In pharmacoepidemiology, safety and effectiveness are frequently evaluated using readily available administrative and electronic health records data. In these settings, detailed co…
An Online Meta-Level Adaptive Design Framework with Targeted Learning Inference: Applications to Evaluating and Utilizing Surrogate Outcomes in Adaptive Designs
Wenxin Zhang, Aaron Hudson, Maya Petersen +1
Adaptive designs are increasingly used in clinical trials and online experiments to improve participant outcomes by dynamically updating treatment allocation as data accumulate. In…
Large Language Models as Co-Pilots for Causal Inference in Medical Studies
Ahmed Alaa, Rachael V. Phillips, Emre Kıcıman +3
The validity of medical studies based on real-world clinical data, such as observational studies, depends on critical assumptions necessary for drawing causal conclusions about med…
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…
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…
Adaptive-TMLE for the Average Treatment Effect based on Randomized Controlled Trial Augmented with Real-World Data
Mark van der Laan, Sky Qiu, Jens Magelund Tarp +1
We consider the problem of estimating the average treatment effect (ATE) when both randomized control trial (RCT) data and external real-world data (RWD) are available. We decompos…
Estimating conditional hazard functions and densities with the highly-adaptive lasso
Anders Munch, Thomas A. Gerds, Mark J. van der Laan +1
We consider estimation of conditional hazard functions and densities over the class of multivariate càdlàg functions with uniformly bounded sectional variation norm when data are e…
Statistical learning for constrained functional parameters in infinite-dimensional models
Razieh Nabi, Nima S. Hejazi, Mark J. van der Laan +1
We develop a general framework for estimating function-valued parameters under equality or inequality constraints in infinite-dimensional statistical models. Such constrained learn…
Longitudinal Targeted Minimum Loss-based Estimation with Temporal-Difference Heterogeneous Transformer
Toru Shirakawa, Yi Li, Yulun Wu +5
We propose Deep Longitudinal Targeted Minimum Loss-based Estimation (Deep LTMLE), a novel approach to estimate the counterfactual mean of outcome under dynamic treatment policies i…
Nonparametric efficient causal estimation of the intervention-specific expected number of recurrent events with continuous-time targeted maximum likelihood and highly adaptive lasso estimation
Helene C. W. Rytgaard, Mark J. van der Laan
Longitudinal settings involving outcome, competing risks and censoring events occurring and recurring in continuous time are common in medical research, but are often analyzed with…