Covariate adjustment for the win ratio

Music City Center 

The win ratio, first popularized by Pocock et al. (2012), has emerged as a powerful tool for evaluating composite and hierarchical outcomes. As adoption grows, covariate adjustment can help further increase precision and reduce bias. Yet integrating covariate information into a hierarchical comparison framework presents theoretical and practical challenges, from defining suitable risk strata to ensuring valid inference under complex study designs. In this talk, we discuss state-of-the-art strategies for covariate adjustment—including model-based and stratified techniques—and highlight practical guidance for implementation in real-world clinical trials. Real examples will be provided as illustrations.