24 citations · 25 across the 3 of their papers we have counts for
4 papers
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…
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…
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…
Constructing Likelihood Functions for Interval-valued Random Variables
Xin Zhang, Boris Beranger, Scott A. Sisson
There is a growing need for the ability to analyse interval-valued data. However, existing descriptive frameworks to achieve this ignore the process by which interval-valued data a…