2 citations · 2 across the 2 of their papers we have counts for
3 papers
stat.ME2025
Regularized Targeted Maximum Likelihood Estimation in Highly Adaptive Lasso Implied Working Models
Yi Li, Sky Qiu, Zeyi Wang +1
We address the challenge of performing Targeted Maximum Likelihood Estimation (TMLE) after an initial Highly Adaptive Lasso (HAL) fit. Existing approaches that utilize the data-ada…
stat.ME2023
Super Ensemble Learning Using the Highly-Adaptive-Lasso
Zeyi Wang, Wenxin Zhang, Brian S Caffo +2
We introduce the Meta Highly-Adaptive-Lasso Minimum Loss Estimator (M-HAL-MLE), a novel ensemble approach for estimating functional parameters of realistically modeled data distrib…
stat.AP2023★ 2 cited
Applying the causal roadmap to longitudinal national Danish registry data: a case study of second-line diabetes medication and dementia
Nerissa Nance, Andrew Mertens, Thomas Gerds +7
The causal roadmap is a formal framework for causal and statistical inference that supports clear specification of the causal question, interpretable and transparent statement of r…