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

被引：17

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

页码：765 / 787

页数：23

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