WWR-package: Weighted Win Loss Statistics and their Variances
In WWR: Weighted Win Loss Statistics and their Variances
Description
Details
Author(s)
References
Description
Calculate the (weighted) win loss statistics including the win ratio, win difference and win product
and their variances, with which the p-values are also calculated. The variance estimation is based on
Luo et al. (2015) <doi:10.1111/biom.12225> and Luo et al. (2017) <doi:10.1002/sim.7284>. This package also calculates general win loss statistics with
user-specified win loss function with variance estimation based on
Bebu and Lachin (2016) <doi:10.1093/biostatistics/kxv032>.
This version corrected an error when outputting confidence interval for win difference.
Details
The DESCRIPTION file:
This package was not yet installed at build time.
Index: This package was not yet installed at build time.
Author(s)
Xiaodong Luo [aut, cre],
Junshan Qiu [ctb],
Steven Bai [ctb],
Hong Tian [ctb],
Mike Mikailov [ctb],
Sanofi [cph]
Maintainer: Xiaodong Luo <Xiaodong.Luo@sanofi.com>
References
Pocock S.J., Ariti C.A., Collier T. J. and Wang D. 2012. The win ratio: a new approach to the analysis of composite endpoints in clinical trials based on clinical priorities. European Heart Journal, 33, 176-182.
Luo X., Tian H., Mohanty S. and Tsai W.-Y. 2015. An alternative approach to confidence interval estimation for the win ratio statistic. Biometrics, 71, 139-145.
Bebu I. and Lachin J.M. 2016. Large sample inference for a win ratio analysis of a composite outcome based on prioritized components. Biostatistics, 17, 178-187.
Luo X., Qiu J., Bai S. and Tian H. 2017. Weighted win loss approach for analyzing prioritized outcomes. Statistics in Medicine, <doi: 10.1002/sim.7284>.
WWR documentation built on May 2, 2019, 11:02 a.m.
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Description Details Author(s) References
Description
Calculate the (weighted) win loss statistics including the win ratio, win difference and win product and their variances, with which the p-values are also calculated. The variance estimation is based on Luo et al. (2015) <doi:10.1111/biom.12225> and Luo et al. (2017) <doi:10.1002/sim.7284>. This package also calculates general win loss statistics with user-specified win loss function with variance estimation based on Bebu and Lachin (2016) <doi:10.1093/biostatistics/kxv032>. This version corrected an error when outputting confidence interval for win difference.
Details
The DESCRIPTION file:
This package was not yet installed at build time.
Index: This package was not yet installed at build time.
Author(s)
Xiaodong Luo [aut, cre], Junshan Qiu [ctb], Steven Bai [ctb], Hong Tian [ctb], Mike Mikailov [ctb], Sanofi [cph]
Maintainer: Xiaodong Luo <Xiaodong.Luo@sanofi.com>
References
Pocock S.J., Ariti C.A., Collier T. J. and Wang D. 2012. The win ratio: a new approach to the analysis of composite endpoints in clinical trials based on clinical priorities. European Heart Journal, 33, 176-182.
Luo X., Tian H., Mohanty S. and Tsai W.-Y. 2015. An alternative approach to confidence interval estimation for the win ratio statistic. Biometrics, 71, 139-145.
Bebu I. and Lachin J.M. 2016. Large sample inference for a win ratio analysis of a composite outcome based on prioritized components. Biostatistics, 17, 178-187.
Luo X., Qiu J., Bai S. and Tian H. 2017. Weighted win loss approach for analyzing prioritized outcomes. Statistics in Medicine, <doi: 10.1002/sim.7284>.
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