Covariate adjustment can substantially improve the efficiency of randomized clinical trials without changing the target estimand or requiring stronger assumptions than the corresponding unadjusted analysis. This presentation develops a general framework that unifies commonly used approaches, including linear adjustment, G-computation, and augmented inverse probability weighting, and discusses extensions to survival outcomes and covariate-adaptive randomization. This webinar will highlight when covariate adjustment provides guaranteed efficiency gains and translate the theoretical results into practical guidance for trial design and analysis. Dr. Ye will also discuss how to perform covariate adjustment when baseline covariates are missing, an important practical issue that can complicate otherwise standard adjustment procedures. The goal is to provide a unified understanding of why covariate adjustment works, when it helps, and how to implement it reliably in practice.

This webinar will be captioned in real time. Individuals needing reasonable accommodations should email [email protected].Requests should be made at least 5 business days before the event.

This event will be recorded and made publicly available on the @NIHODP YouTube channel within a few weeks.