6 papers
GAUGER: Generalized Regression Adjustment via Graph-Weighted Exposure-Level Residualization for Design-Based Inference Under Interference
Lei Shi, Rita Lyu, Sizhu Lu +1
Estimating causal effects under interference is a common problem in social science and economics. However, it is challenging due to the complex dependency structure induced by netw…
Estimating within-cluster and between-cluster spillover effects in randomized saturation designs
Sizhu Lu, Lei Shi, Peng Ding
Randomized saturation designs are two-stage experiments: they first randomly assign treatment probabilities over the clusters and then randomly assign the treatment to the units wi…
Estimating treatment effects with competing intercurrent events in randomized controlled trials
Sizhu Lu, Yanyao Yi, Yongming Qu +3
The analysis of randomized controlled trials is often complicated by intercurrent events (IEs) -- events that occur after treatment initiation and affect either the interpretation…
Efficient Inference for Noisy LLM-as-a-Judge Evaluation
Yiqun T Chen, Sizhu Lu, Sijia Li +2
Large language models (LLMs) are increasingly used as automatic evaluators of generative AI outputs, a paradigm often referred to as "LLM-as-a-judge." In practice, LLM judges are i…
TERRA: A Transformer-Enabled Recursive R-learner for Longitudinal Heterogeneous Treatment Effect Estimation
Lei Shi, Sizhu Lu, Qiuran Lyu +2
Accurately estimating heterogeneous treatment effects (HTE) in longitudinal settings is essential for personalized decision-making across healthcare, public policy, education, and…
Design-based causal inference in bipartite experiments
Sizhu Lu, Lei Shi, Yue Fang +2
Bipartite experiments arise in various fields, in which the treatments are randomized over one set of units, while the outcomes are measured over another separate set of units. How…