8 citations · 16 across the 6 of their papers we have counts for
6 papers
Targeting Learning: Robust Statistics for Reproducible Research
Jeremy R. Coyle, Nima S. Hejazi, Ivana Malenica +9
Targeted Learning is a subfield of statistics that unifies advances in causal inference, machine learning and statistical theory to help answer scientifically impactful questions w…
Efficient Estimation of Pathwise Differentiable Target Parameters with the Undersmoothed Highly Adaptive Lasso
Mark J. van der Laan, David Benkeser, Weixin Cai
We consider estimation of a functional parameter of a realistically modeled data distribution based on observing independent and identically distributed observations. We define an…
Nonparametric Bootstrap Inference for the Targeted Highly Adaptive LASSO Estimator
Weixin Cai, Mark van der Laan
The Highly-Adaptive-LASSO Targeted Minimum Loss Estimator (HAL-TMLE) is an efficient plug-in estimator of a pathwise differentiable parameter in a statistical model that at minimal…
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…
One-step Targeted Maximum Likelihood for Time-to-event Outcomes
Weixin Cai, Mark J. van der Laan
Current Targeted Maximum Likelihood Estimation (TMLE) methods used to analyze time-to-event data estimate the survival probability for each time point separately, which result in e…
Data-adaptive statistics for multiple hypothesis testing in high-dimensional settings
Weixin Cai, Nima S. Hejazi, Alan E. Hubbard
Current statistical inference problems in areas like astronomy, genomics, and marketing routinely involve the simultaneous testing of thousands -- even millions -- of null hypothes…