3 citations · 3 across the 3 of their papers we have counts for
7 papers
Inference for natural mediation effects under case-cohort sampling with applications in identifying COVID-19 vaccine correlates of protection
David Benkeser, Iván Díaz, Jialu Ran
Combating the SARS-CoV2 pandemic will require the fast development of effective preventive vaccines. Regulatory agencies may open accelerated approval pathways for vaccines if an i…
Efficient nonparametric inference on the effects of stochastic interventions under two-phase sampling, with applications to vaccine efficacy trials
Nima S. Hejazi, Mark J. van der Laan, Holly E. Janes +2
The advent and subsequent widespread availability of preventive vaccines has altered the course of public health over the past century. Despite this success, effective vaccines to…
Nonparametric inference for interventional effects with multiple mediators
David Benkeser
Understanding the pathways whereby an intervention has an effect on an outcome is a common scientific goal. A rich body of literature provides various decompositions of the total i…
Design and analysis considerations for a sequentially randomized HIV prevention trial
David Benkeser, Keith Horvath, Cathy Reback +2
TechStep is a randomized trial of a mobile health interventions targeted towards transgender adolescents. The interventions include a short message system, a mobile-optimized web a…
A nonparametric super-efficient estimator of the average treatment effect
David Benkeser, Weixin Cai, Mark J van der Laan
Doubly robust estimators of causal effects are a popular means of estimating causal effects. Such estimators combine an estimate of the conditional mean of the outcome given treatm…
Robust inference on the average treatment effect using the outcome highly adaptive lasso
Cheng Ju, David Benkeser, Mark J. van der Laan
Many estimators of the average effect of a treatment on an outcome require estimation of the propensity score, the outcome regression, or both. It is often beneficial to utilize fl…