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On the alternative hypotheses for the win ratio

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  • Lu Mao

Abstract

We extend the results of Luo et al. (2015, Biometrics 71, 139–145) regarding the alternative hypotheses for the win ratio from hazard orders to the upper quadrant stochastic order on the plane. This extension substantially widens the range of alternatives against which the win ratio is known to be consistent. It incorporates alternatives induced by simple and popular copula models that are left out by the characterization of Luo et al. (2015). We also discuss how our results may be generalized to win ratios in multivariate and stratified settings.

Suggested Citation

  • Lu Mao, 2019. "On the alternative hypotheses for the win ratio," Biometrics, The International Biometric Society, vol. 75(1), pages 347-351, March.
    • Handle: RePEc:bla:biomet:v:75:y:2019:i:1:p:347-351
    DOI: 10.1111/biom.12954
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    References listed on IDEAS

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    1. D. Oakes, 2016. "On the win-ratio statistic in clinical trials with multiple types of event," Biometrika, Biometrika Trust, vol. 103(3), pages 742-745.
    2. Xiaodong Luo & Hong Tian & Surya Mohanty & Wei Yann Tsai, 2015. "An alternative approach to confidence interval estimation for the win ratio statistic," Biometrics, The International Biometric Society, vol. 71(1), pages 139-145, March.
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    Cited by:

    1. Lu Mao & Tuo Wang, 2021. "A class of proportional win‐fractions regression models for composite outcomes," Biometrics, The International Biometric Society, vol. 77(4), pages 1265-1275, December.
    2. Xiaodong Luo & Hui Quan, 2020. "Some Meaningful Weighted Log-Rank and Weighted Win Loss Statistics," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 12(2), pages 216-224, July.
    3. Lu Mao & KyungMann Kim & Xinran Miao, 2022. "Sample size formula for general win ratio analysis," Biometrics, The International Biometric Society, vol. 78(3), pages 1257-1268, September.

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