Power and sample size calculation for the win odds test: application to an ordinal endpoint in COVID-19 trials

被引：15
|
作者：
Gasparyan, Samvel B. [1 ]
Kowalewski, Elaine K. [2 ]
Folkvaljon, Folke [1 ]
Bengtsson, Olof [1 ]
Buenconsejo, Joan [3 ]
Adler, John [1 ]
Koch, Gary G. [2 ]
机构：
[1] AstraZeneca, BioPharmaceut R&D, Renal & Metab, Biometr,Late Stage Dev,Cardiovasc, Gothenburg, Sweden
[2] Univ N Carolina, Gillings Sch Global Publ Hlth, Dept Biostat, Chapel Hill, NC 27515 USA
[3] AstraZeneca, BioPharmaceut R&D, Renal & Metab, Biometr,Late Stage Dev,Cardiovasc, Gaithersburg, MD USA
来源：
JOURNAL OF BIOPHARMACEUTICAL STATISTICS | 2021年 / 31卷 / 06期
关键词：
Win odds; COVID-19; power; sample size; effect size; number needed to treat; Mann-Whitney; Fligner-Policello; Somers' D C; R; Wilcoxon rank-sum; SAS software; CLINICAL-TRIALS; STRATEGIES; RATIO;
D O I：
10.1080/10543406.2021.1968893
中图分类号：
R9 [药学];
学科分类号：
1007 ;
摘要：
The win odds is a distribution-free method of comparing locations of distributions of two independent random variables. Introduced as a method for analyzing hierarchical composite endpoints, it is well suited to be used in the analysis of ordinal scale endpoints in COVID-19 clinical trials. For a single outcome, we provide power and sample size calculation formulas for the win odds test. We also provide an implementation of the win odds analysis method for a single ordinal outcome in a commonly used statistical software to make the win odds analysis fully reproducible.
引用
收藏
页码：765 / 787
页数：23
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