10 citations · 45 across the 35 of their papers we have counts for
6 papers · 1 filter
Learning Across Experiments and Time: Tackling Heterogeneity in A/B Testing
Xinran Li
A/B testing plays a central role in data-driven product development, guiding launch decisions for new features and designs. However, treatment effect estimates are often noisy due…
Cluster-robust inference with a single treated cluster using the t-test
Chun Pong Lau, Xinran Li
This paper considers inference when there is a single treated cluster and a fixed number of control clusters, a setting that is common in empirical work, especially in difference-i…
Design-based nested instrumental variable analysis
Zhe Chen, Xinran Li, Michael O. Harhay +1
Two binary instrumental variables (IVs) are nested if individuals who comply under one binary IV also comply under the other. This situation often arises when the two IVs represent…
Robust Sensitivity Analysis via Augmented Percentile Bootstrap under Simultaneous Violations of Unconfoundedness and Overlap
Han Cui, Xinran Li
The identification of causal effects in observational studies typically relies on two standard assumptions: unconfoundedness and overlap. However, both assumptions are often questi…
Randomization Inference with Sample Attrition
Xinran Li, Peizan Sheng, Zeyang Yu
Randomization inference is a widely-used and appealing approach for analyzing treatment effects in randomized experiments, as it is finite-sample valid and does not require any dis…
Finite-Sample Valid Randomization Tests for Monotone Spillover Effects
Shunzhuang Huang, Xinran Li, Panos Toulis
Randomization tests have gained popularity for causal inference under network interference because they are finite-sample valid with minimal assumptions. However, existing procedur…