Literature DB >> 25156540

An alternative approach to confidence interval estimation for the win ratio statistic.

Xiaodong Luo1, Hong Tian2, Surya Mohanty2, Wei Yann Tsai3.   

Abstract

Pocock et al. (2012, European Heart Journal 33, 176-182) proposed a win ratio approach to analyzing composite endpoints comprised of outcomes with different clinical priorities. In this article, we establish a statistical framework for this approach. We derive the null hypothesis and propose a closed-form variance estimator for the win ratio statistic in all pairwise matching situation. Our simulation study shows that the proposed variance estimator performs well regardless of the magnitude of treatment effect size and the type of the joint distribution of the outcomes.
© 2014, The International Biometric Society.

Keywords:  Clinical trials; Composite endpoints; Hypothesis testing; Variance estimation; Win ratio

Mesh:

Substances:

Year:  2014        PMID: 25156540     DOI: 10.1111/biom.12225

Source DB:  PubMed          Journal:  Biometrics        ISSN: 0006-341X            Impact factor:   2.571


  10 in total

1.  Large sample inference for a win ratio analysis of a composite outcome based on prioritized components.

Authors:  Ionut Bebu; John M Lachin
Journal:  Biostatistics       Date:  2015-09-08       Impact factor: 5.899

2.  The inverse-probability-of-censoring weighting (IPCW) adjusted win ratio statistic: an unbiased estimator in the presence of independent censoring.

Authors:  Gaohong Dong; Lu Mao; Bo Huang; Margaret Gamalo-Siebers; Jiuzhou Wang; GuangLei Yu; David C Hoaglin
Journal:  J Biopharm Stat       Date:  2020-06-17       Impact factor: 1.051

3.  Properties of composite time to first event versus joint marginal analyses of multiple outcomes.

Authors:  Ionut Bebu; John M Lachin
Journal:  Stat Med       Date:  2018-06-28       Impact factor: 2.373

4.  Weighted win loss approach for analyzing prioritized outcomes.

Authors:  Xiaodong Luo; Junshan Qiu; Steven Bai; Hong Tian
Journal:  Stat Med       Date:  2017-03-26       Impact factor: 2.373

5.  Statistical models for composite endpoints of death and non-fatal events: a review.

Authors:  Lu Mao; KyungMann Kim
Journal:  Stat Biopharm Res       Date:  2021-07-06       Impact factor: 1.586

6.  On recurrent-event win ratio.

Authors:  Lu Mao; KyungMann Kim; Yi Li
Journal:  Stat Methods Med Res       Date:  2022-03-29       Impact factor: 2.494

7.  Sample size formula for general win ratio analysis.

Authors:  Lu Mao; KyungMann Kim; Xinran Miao
Journal:  Biometrics       Date:  2021-06-08       Impact factor: 1.701

8.  A class of proportional win-fractions regression models for composite outcomes.

Authors:  Lu Mao; Tuo Wang
Journal:  Biometrics       Date:  2020-10-10       Impact factor: 1.701

9.  Common scale minimal sufficient balance: An improved method for covariate-adaptive randomization based on the Wilcoxon-Mann-Whitney odds ratio statistic.

Authors:  Hannah Johns; Dominic Italiano; Bruce Campbell; Leonid Churilov
Journal:  Stat Med       Date:  2022-02-17       Impact factor: 2.497

10.  Win Ratio -An Intuitive and Easy-To-Interpret Composite Outcome in Medical Studies.

Authors:  Hongyue Wang; Jing Peng; Juila Z Zheng; Bokai Wang; Xiang Lu; Chongshu Chen; Xin M Tu; Changyong Feng
Journal:  Shanghai Arch Psychiatry       Date:  2017-02-25
  10 in total

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