4 papers
Bridging Control Variates and Regression Adjustment in A/B Testing: From Design-Based to Model-Based Frameworks
Yu Zhang, Bokui Wan, Yongli Qin
A B testing serves as the gold standard for large scale, data driven decision making in online businesses. To mitigate metric variability and enhance testing sensitivity, control v…
A Two-armed Bandit Framework for A/B Testing
Jinjuan Wang, Qianglin Wen, Yu Zhang +2
A/B testing is widely used in modern technology companies for policy evaluation and product deployment, with the goal of comparing the outcomes under a newly-developed policy again…
Structural Representations and Identification of Marginal Policy Effects
Zhixin Wang, Yu Zhang, Zhengyu Zhang
This paper investigates the structural interpretation of the marginal policy effect (MPE) within nonseparable models. We demonstrate that, for a smooth functional of the outcome di…
Strategic A/B testing via Maximum Probability-driven Two-armed Bandit
Yu Zhang, Shanshan Zhao, Bokui Wan +2
Detecting a minor average treatment effect is a major challenge in large-scale applications, where even minimal improvements can have a significant economic impact. Traditional met…