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Weighted win loss approach for analyzing prioritized outcomes.


ABSTRACT: 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.

SUBMITTER: Luo X 

PROVIDER: S-EPMC5490500 | biostudies-literature | 2017 Jul

REPOSITORIES: biostudies-literature

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Weighted win loss approach for analyzing prioritized outcomes.

Luo Xiaodong X   Qiu Junshan J   Bai Steven S   Tian Hong H  

Statistics in medicine 20170326 15


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 calculate  ...[more]

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