Luo Xiaodong, Qiu Junshan, Bai Steven, Tian Hong
Research and Development, Sanofi US, Bridgewater, 08807, NJ, U.S.A.
Division of Biometrics I, Office of Biostatistics, Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, MD, 20993, U.S.A.
Stat Med. 2017 Jul 10;36(15):2452-2465. doi: 10.1002/sim.7284. Epub 2017 Mar 26.
To analyze prioritized outcomes, Buyse (2010) and Pocock et al. (2012) proposed the win loss approach. In this paper, we first study the relationship between the win loss approach and the traditional survival analysis on the time to the first event. We then propose the weighted win loss statistics to improve the efficiency of the unweighted methods. A closed-form variance estimator of the weighted win loss statistics is derived to facilitate hypothesis testing and study design. We also calculated the contribution index to better interpret the results of the weighted win loss approach. Simulation studies and real data analysis demonstrated the characteristics of the proposed statistics. Copyright © 2017 John Wiley & Sons, Ltd.
为了分析优先结果,比瑟(2010年)和波科克等人(2012年)提出了胜负法。在本文中,我们首先研究胜负法与传统生存分析中首次事件发生时间之间的关系。然后我们提出加权胜负统计量以提高未加权方法的效率。推导了加权胜负统计量的闭式方差估计量,以促进假设检验和研究设计。我们还计算了贡献指数,以便更好地解释加权胜负法的结果。模拟研究和实际数据分析证明了所提出统计量的特性。版权所有© 2017约翰·威利父子有限公司。