6 papers
Win Time In Favor of Treatment (WINFT) for Hierarchical Endpoints
Sahil S. Patel, Huiman Barnhart, Lu Mao +2
Standard win statistics methods determine a win, loss, or tie for a pair of subjects based on their worst outcomes (up to the end of study) that may not fully utilize all patients'…
Estimation and Inference for Win Measures with Multiple Ordinal Endpoints Subject to Missingness
Yi Liu, Huiman Barnhart, Sean O'Brien +2
Win measures, including the win ratio, win odds, net benefit, and desirability of outcome ranking, are increasingly used in randomized clinical trials with multiple hierarchical or…
The FORSS Framework for Sample Size and Power Calculations With Win Statistics for Hierarchical Endpoints
Baoshan Zhang, Huiman X. Barnhart, Yuan Wu +1
Win statistics have gained increasing popularity as primary analysis methods for clinical trials with hierarchical endpoints (HEs) as primary endpoints. However, existing sample si…
Estimation and Inference of the Win Ratio for Two Hierarchical Endpoints Subject to Censoring and Missing Data
Yi Liu, Huiman Barnhart, Sean O'Brien +2
The win ratio (WR) is a widely used metric to compare treatments in randomized clinical trials with hierarchically ordered endpoints. Counting-based approaches, such as Pocock's al…
A tutorial for propensity score weighting methods under violations of the positivity assumption
Yi Liu, Yuan Wang, Ying Gao +2
Violations of the positivity assumption can render conventional causal estimands unidentifiable, including the average treatment effect (ATE), the average treatment effect on the t…
Variance Estimation for Weighted Average Treatment Effects
Huiyue Li, Yi Liu, Yunji Zhou +3
Common variance estimation methods for weighted average treatment effects (WATEs) in observational studies include nonparametric bootstrap and model-based, closed-form sandwich var…