134 citations · 468 across the 85 of their papers we have counts for
13 papers · 1 filter
Small area learning
Katarzyna Reluga, Nicola Salvati, Setareh Ranjbar +2
Small area estimation (SAE) traditionally borrows strength across domains through a prespecified working model. We introduce small area learning (SAL), a learner-agnostic framework…
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…
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…
Towards Best Practices for Covariate Adjustment in Regulatory Trials: From Fixed to Data-Adaptive Approaches
Laura B. Balzer, Lei Nie, Issa J. Dahabreh +15
While randomization justifies the use of unadjusted effect estimators in randomized trials, there is growing interest in covariate adjustment to improve precision. Adjusting for ba…
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…
Targeted Highly Adaptive Lasso Minimum Loss Estimation of Target Functions
Vanessa Rodriguez, Karla Diaz-Ordaz, Brieuc Lehmann +1
We propose a Targeted Highly Adaptive Lasso for estimation of non-pathwise differentiable functional parameters such as the dose-response curve (DRC) for continuous exposure. We as…
Targeted maximum likelihood estimation for longitudinal two-stage designs with outcome subsampling
Kirsten E. Landsiedel, Maya L. Petersen, Mark J. van der Laan
We consider efficient estimation of causal parameters in longitudinal two-stage designs with outcome subsampling, motivated by resampling designs in HIV-related mortality studies.…
Higher-Order Efficient Estimators: A Review and Simulation-Based Benchmark Study
Zeyi Wang, Mark J. van der Laan
Higher-order efficient estimators extend standard first-order semiparametric estimators by replacing second-order residuals with third- or higher-order terms, potentially enabling…
Improving the Efficiency of Subgroup Analysis in Randomized Controlled Trials with TMLE
Sky Qiu, Nerissa Nance, Rachael Phillips +3
Subgroup analyses within randomized controlled trials are often underpowered due to limited sample sizes. We address this challenge by leveraging trial participants outside the sub…
Estimation of treatment effects in presence of differential use of post-randomization concomitant medication with time-to-event outcomes
Helene C. W. Rytgaard, Edwin Fong, Jens M. Tarp +3
In placebo-controlled randomized trials, the post-randomization use of concomitant medications may be higher in the placebo arm than in the treatment arm. This may dilute the full…
Considerations for the Integration of Randomized Controlled Trials and Real-World Data
Sky Qiu, Charles Barr, Lauren Dang +18
As clinical decision-making increasingly moves toward individualized and context-specific treatment recommendations, reliance on any single evidence source, randomized or observati…
Efficient Targeted Maximum Likelihood Estimators for Two-Phase Design Problems
Sky Qiu, Susan Gruber, Pamela A. Shaw +2
In a typical two-phase design, a random sample is drawn from the target population in phase 1, during which only a subset of variables is collected. In phase 2, a subsample of the…
HAL-MLE Log-Splines Density Estimation (Part I: Univariate)
Yilong Hou, Zhengpu Zhao, Yi Li +1
We study nonparametric maximum likelihood estimation of probability densities under a total variation (TV) type penalty, sectional variation norm (also named as Hardy-Krause variat…