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The win odds: statistical inference and regression.
Song, James; Verbeeck, Johan; Huang, Bo; Hoaglin, David C; Gamalo-Siebers, Margaret; Seifu, Yodit; Wang, Duolao; Cooner, Freda; Dong, Gaohong.
Affiliation
  • Song J; BeiGene, Ridgefield Park, New Jersey, USA.
  • Verbeeck J; DSI, I-Biostat, University Hasselt, Hasselt, Belgium.
  • Huang B; Pfizer Inc, Groton, Connecticut, USA.
  • Hoaglin DC; Department of Population and Quantitative Health Sciences, UMass Chan Medical School, Worcester, Massachusetts, USA.
  • Gamalo-Siebers M; Pfizer Inc, Collegeville, Pennsylvania, USA.
  • Seifu Y; Bristol Myers Squibb, Berkeley Heights, New Jersey, USA.
  • Wang D; Liverpool School of Tropical Medicine, Liverpool, UK.
  • Cooner F; Amgen, Thousand Oaks, California, USA.
  • Dong G; BeiGene, Ridgefield Park, New Jersey, USA.
J Biopharm Stat ; 33(2): 140-150, 2023 03.
Article in En | MEDLINE | ID: mdl-35946932
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.
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Full text: 1 Database: MEDLINE Main subject: Models, Statistical Limits: Humans Language: En Journal: J Biopharm Stat Journal subject: FARMACOLOGIA Year: 2023 Type: Article Affiliation country: United States

Full text: 1 Database: MEDLINE Main subject: Models, Statistical Limits: Humans Language: En Journal: J Biopharm Stat Journal subject: FARMACOLOGIA Year: 2023 Type: Article Affiliation country: United States