6 papers
GAUGER: Generalized Regression Adjustment via Graph-Weighted Exposure-Level Residualization for Design-Based Inference Under Interference
Lei Shi, Rita Lyu, Sizhu Lu
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…
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…
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…
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…