3 papers
stat.ME2026
Bias reduction in g-computation for covariate adjustment in randomized clinical trials
Xin Zhang, Lin Liu, Haitao Chu
G-computation is a powerful method for estimating unconditional treatment effects with covariate adjustment in randomized clinical trials. It typically relies on fitting canonical…
stat.ME2025
Covariate Adjustment in Randomized Experiments Motivated by Higher-Order Influence Functions
Sihui Zhao, Xinbo Wang, Lin Liu +1
Higher-Order Influence Functions (HOIF), developed in a series of papers over the past twenty years, are a fundamental theoretical device for constructing rate-optimal causal-effec…
stat.ME2025
A robust score test in g-computation for covariate adjustment in randomized clinical trials leveraging different variance estimators via influence functions
Xin Zhang, Haitao Chu, Lin Liu +1
G-computation has become a widely used robust method for estimating unconditional (marginal) treatment effects with covariate adjustment in the analysis of randomized clinical tria…