The win odds: statistical inference and regression

被引：6

作者：

Song, James ^{[1
]}

Verbeeck, Johan ^{[2
]}

Huang, Bo ^{[3
]}

Hoaglin, David C. ^{[4
]}

Gamalo-Siebers, Margaret ^{[5
]}

Seifu, Yodit ^{[6
]}

Wang, Duolao ^{[7
]}

Cooner, Freda ^{[8
]}

Dong, Gaohong ^{[1
]}

机构：

[1] BeiGene, Ridgefield Pk, NJ 07660 USA

[2] Univ Hasselt, I Biostat, DSI, Hasselt, Belgium

[3] Pfizer Inc, Groton, CT 06340 USA

[4] UMass Chan Med Sch, Dept Populat & Quantitat Hlth Sci, Worcester, MA USA

[5] Pfizer Inc, Collegeville, PA USA

[6] Bristol Myers Squibb, New York, NJ USA

[7] Univ Liverpool Liverpool Sch Trop Med, Liverpool, Merseyside, England

[8] Amgen Inc, Thousand Oaks, CA USA

来源：

JOURNAL OF BIOPHARMACEUTICAL STATISTICS | 2023年 / 33卷 / 02期

关键词：

Win ratio; win odds; net benefit; win statistics; probabilistic index model; bootstrap; permutation; PROBABILISTIC INDEX; CLINICAL-TRIALS; RATIO; MORBIDITY; MORTALITY;

D O I：

10.1080/10543406.2022.2089156

中图分类号：

R9 [药学];

学科分类号：

1007 ;

摘要：

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.

引用

页码：140 / 150

页数：11

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