3 citations · 4 across the 7 of their papers we have counts for
7 papers
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…
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…
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…
An Estimator-Robust Design for Augmenting Randomized Controlled Trials with External Real-World Data
Sky Qiu, Jens Tarp, Andrew Mertens +1
Augmenting randomized controlled trials (RCTs) with external real-world data (RWD) has the potential to improve the finite sample efficiency of treatment effect estimators. We desc…
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…
Longitudinal Targeted Minimum Loss-based Estimation with Temporal-Difference Heterogeneous Transformer
Toru Shirakawa, Yi Li, Yulun Wu +5
We propose Deep Longitudinal Targeted Minimum Loss-based Estimation (Deep LTMLE), a novel approach to estimate the counterfactual mean of outcome under dynamic treatment policies i…