10 citations · 45 across the 35 of their papers we have counts for
35 papers
Randomization inference for treatment effects on survival outcomes
Lucy D'Agostino McGowan, Joseph Rigdon, Xinran Li +1
The log-rank test and Kaplan--Meier plot are standard tools for analyzing time-to-event data in randomized clinical trials, yet neither provides a summary of the magnitude of the t…
Randomization Tests for Distributions of Individual Treatment Effects via Combined Rank Statistics
David Kim, Yongchang Su, Jake Bowers +1
What proportion of treated units actually benefited from an experimental intervention? What is the median or the largest individual treatment effect? This paper develops methods fo…
Identifiability of Treatment Effects with Unobserved Spatially Varying Confounders
Tommy Tang, Xinran Li, Bo Li
The study of causal effects in the presence of unmeasured spatially varying confounders has garnered increasing attention. However, a general framework for identifiability, which i…
Design-based theory for causal inference from adaptive experiments
Xinran Li, Anqi Zhao
Adaptive designs dynamically update treatment probabilities using information accumulated during the experiment. Existing theory for causal inference from adaptive experiments prim…
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…