collaborators

5 papers

stat.ML2026

A Unified Causal Inference Framework for the Desirability of Outcome Ranking Paradigm in Benefit-Risk Evaluation

Yuan Feng, Shiyu Shu, Yixin Fang +4

We developed a unified covariate-adjusted causal inference framework for estimating the desirability of outcome ranking (DOOR) probability for benefit-risk evaluation in randomized…

stat.ME2026

On Cluster Randomized Trials with the Desirability of Outcome Ranking (DOOR) Endpoints

Wanying Shao, Toshimitsu Hamasaki, Scott Evans +1

Cluster randomized trials are widely used when individual randomization is logistically infeasible or when correlations between observations cannot be ignored, especially in fields…

stat.ME2026

Navigating the Landscape of Hierarchical Multi-Component Strategies: GPC, DOOR, and MOST

Mickaël De Backer, Johan Verbeeck, Vivian Lanius +5

There is a growing recognition of the importance to involve patients in every stage of drug development. This shift acknowledges that patients' perspectives, experiences, and prefe…

stat.ME2026

Doubly Robust Estimation of Desirability of Outcome Ranking (DOOR) Probability with Application to MDRO Studies

Shiyu Shu, Toshimitsu Hamasaki, Scott Evans +3

In observational studies, adjusting for confounders is required if a treatment comparison is planned. A crude comparison of the primary endpoint without covariate adjustment will s…

stat.ME2025

Desirability of outcome ranking (DOOR) analysis for multivariate survival outcomes with application to ACTT-1 trial

Shiyu Shu, Guoqing Diao, Toshimitsu Hamasaki +1

Desirability Of Outcome Ranking (DOOR) methodology accounts for problems that conventional benefit:risk analyses in clinical trials ignore, such as competing risks and the trade-of…