Preprint
Sep 2026
Adjusting for Many Covariates in Randomized Clinical Trials with GLMs: Bias Reduction by Jackknife and Practical Guidance
A novel jackknife-based approach to covariate adjustment through generalized linear models (GLMs), which is term as JAckknife Score-based Adjustment (JASA), together with its calibrated version JASACal, which can adjust for a much greater number of covariates than existing benchmarks.
Si-Hui Zhao, Xin-Bo Wang, Yong-Yong Ren et al.
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