5 citations · 8 across the 10 of their papers we have counts for
10 papers
A Unified Adaptive Enrichment Design for Power Enhancement
Junzhe Shao, Aibo Gong, Juan Shen +1
Randomized controlled trials (RCTs) are the gold standard for evaluating treatment effects, but fixed eligibility criteria and enrollment decisions can be inefficient, especially w…
HERO: Improving the Reliability and Sensitivity of Generative Model Evaluation Using Historical Data
Xinrui Ruan, Zhenyu Zhao, Waverly Wei +4
Reliable generative AI models critically rely on expert human annotations to evaluate output quality, yet these "gold" labels are expensive to collect and limited in quantity. Orga…
SLOACI: Surrogate-Leveraged Online Adaptive Causal Inference
Yingying Fan, Zihan Wang, Waverly Wei
Adaptive experimental designs have gained increasing attention across a range of domains. In this paper, we propose a new methodological framework, surrogate-leveraged online adapt…
Can Language Models Boost the Power of Randomized Experiments Without Statistical Bias?
Xinrui Ruan, Xinwei Ma, Yingfei Wang +2
Randomized controlled trials (RCTs) are widely adopted for causal inference, yet cost and sample-size constraints limit power. We introduce CALM (Causal Analysis leveraging Languag…
Covariate-Adjusted Response-Adaptive Design with Delayed Outcomes
Xinwei Ma, Jingshen Wang, Waverly Wei
Covariate-adjusted response-adaptive (CARA) designs have gained widespread adoption for their clear benefits in enhancing experimental efficiency and participant welfare. These des…
Adaptive Experiments Toward Learning Treatment Effect Heterogeneity
Waverly Wei, Xinwei Ma, Jingshen Wang
Understanding treatment effect heterogeneity has become an increasingly popular task in various fields, as it helps design personalized advertisements in e-commerce or targeted tre…
Fair Adaptive Experiments
Waverly Wei, Xinwei Ma, Jingshen Wang
Randomized experiments have been the gold standard for assessing the effectiveness of a treatment or policy. The classical complete randomization approach assigns treatments based…
Efficient Targeted Learning of Heterogeneous Treatment Effects for Multiple Subgroups
Waverly Wei, Maya Petersen, Mark J van der Laan +3
In biomedical science, analyzing treatment effect heterogeneity plays an essential role in assisting personalized medicine. The main goals of analyzing treatment effect heterogenei…
Inference on the Best Policies with Many Covariates
Waverly Wei, Yuqing Zhou, Zeyu Zheng +1
Understanding the impact of the most effective policies or treatments on a response variable of interest is desirable in many empirical works in economics, statistics and other dis…
Assessing the Most Vulnerable Subgroup to Type II Diabetes Associated with Statin Usage: Evidence from Electronic Health Record Data
Xinzhou Guo, Waverly Wei, Molei Liu +3
There have been increased concerns that the use of statins, one of the most commonly prescribed drugs for treating coronary artery disease, is potentially associated with the incre…