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http://hdl.handle.net/1942/38085
Title: | The win odds: statistical inference and regression | Authors: | Song, James VERBEECK, Johan Huang , Bo Hoaglin, David C. Gamalo-Siebers, Margaret Seifu, Yodit Wang, Duolao Cooner, Freda Dong, Gaohong |
Issue Date: | 2023 | Publisher: | TAYLOR & FRANCIS INC | Source: | Journal of biopharmaceutical statistics (Print), 33 (2), p. 140-150 | 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. | Notes: | Song, J (corresponding author), BeiGene, Ridgefield Pk, NJ 07660 USA. james.song@beigene.com |
Keywords: | Win ratio;win odds;net benefit;win statistics;probabilistic index model;bootstrap;permutation | Document URI: | http://hdl.handle.net/1942/38085 | ISSN: | 1054-3406 | e-ISSN: | 1520-5711 | DOI: | 10.1080/10543406.2022.2089156 | ISI #: | 000838600800001 | Rights: | 2022 Taylor & Francis Group, LLC | Category: | A1 | Type: | Journal Contribution | Validations: | ecoom 2023 |
Appears in Collections: | Research publications |
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Microsoft Word - WO_revised__2__Final2.pdf | Peer-reviewed author version | 916.84 kB | Adobe PDF | View/Open |
The win odds_ statistical inference and regression.pdf Restricted Access | Published version | 903.83 kB | Adobe PDF | View/Open Request a copy |
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