16 citations · 25 across the 8 of their papers we have counts for
8 papers
Targeted maximum likelihood estimation of vaccine effectiveness and immune correlates in test-negative design studies with missing data
Leah I. B. Andrews, Lars van der Laan, Peter B. Gilbert
The test-negative design (TND) is a resource-efficient observational study design that can assess vaccine effectiveness and exposure-proximal immune correlates of disease. The TND…
Doubly robust inference via calibration
Lars van der Laan, Alex Luedtke, Marco Carone
Doubly robust estimators are widely used for estimating average treatment effects and other linear summaries of regression functions. While consistency requires only one of two nui…
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…
Combining T-learning and DR-learning: a framework for oracle-efficient estimation of causal contrasts
Lars van der Laan, Marco Carone, Alex Luedtke
We introduce efficient plug-in (EP) learning, a novel framework for the estimation of heterogeneous causal contrasts, such as the conditional average treatment effect and condition…
Adaptive debiased machine learning using data-driven model selection techniques
Lars van der Laan, Marco Carone, Alex Luedtke +1
Debiased machine learning estimators for smooth functionals in nonparametric models can exhibit substantial variability and instability, often leading practitioners to instead rely…
Semiparametric logistic regression for inference on relative vaccine efficacy in case-only studies with informative missingness
Lars van der Laan, Peter B. Gilbert
We develop semiparametric methods for estimating subgroup-specific relative vaccine efficacy against multiple viral strains in a partially vaccinated population. Focusing on observ…
Causal isotonic calibration for heterogeneous treatment effects
Lars van der Laan, Ernesto Ulloa-Pérez, Marco Carone +1
We propose causal isotonic calibration, a novel nonparametric method for calibrating predictors of heterogeneous treatment effects. Furthermore, we introduce cross-calibration, a d…
Efficient nonparametric estimation of the covariate-adjusted threshold-response function, a support-restricted stochastic intervention
Lars van der Laan, Wenbo Zhang, Peter B. Gilbert
Identifying a biomarker or treatment-dose threshold that marks a specified level of risk is an important problem, especially in clinical trials. This risk, viewed as a function of…