Adjusting for Many Covariates in Randomized Clinical Trials with GLMs: Bias Reduction by Jackknife and Practical Guidance

Adjusting for baseline covariates has become standard practice in analyzing randomized clinical trials. In the low-dimensional setting, it is well understood that covariate adjustment through a parametric working model can sometimes be more efficient than the unadjusted difference-in-mean estimator.