The win odds: statistical inference and regression. Issue 2 (4th March 2023)

• Record Type: Journal Article
• Authors: Song, James; Verbeeck, Johan; Huang, Bo; Hoaglin, David C.; Gamalo-Siebers, Margaret; Seifu, Yodit; Wang, Duolao; Cooner, Freda; Dong, Gaohong
• Is Part Of: Journal of biopharmaceutical statistics. Volume 33:Issue 2(2023)
• Page Start: 140
• Page End: 150
• Publication Date: 2023-03-04
• Subjects: Win ratio -- win odds -- net benefit -- win statistics -- probabilistic index model -- bootstrap -- permutation; Pharmacy -- Statistical methods -- Periodicals; Drugs -- Testing -- Statistical methods -- Periodicals; Biometry -- Periodicals; Biopharmaceutics -- Periodicals; Pharmacokinetics -- Periodicals; 615.19
• DOI: 10.1080/10543406.2022.2089156
• Languages: English
• ISSNs: 1054-3406

Abstract

ABSTRACT: Generalized pairwise comparisons and win statistics (i.e., win ratio, win odds and net benefit) are advantageous in analyzing and interpreting a composite of multiple outcomes in clinical trials. An important limitation of these statistics is their inability to adjust for covariates other than by stratified analysis. Because the win ratio does not account for ties, the win odds, a modification that includes ties, has attracted attention. We review and combine information on the win odds to articulate the statistical inferences for the win odds. We also show alternative variance estimators based on the exact permutation and bootstrap as well as statistical inference via the probabilistic index. Finally, we extend multiple-covariate regression probabilistic index models to the win odds with a univariate outcome. As an illustration we apply the regression models to the data in the CHARM trial.