Please use this identifier to cite or link to this item:
http://hdl.handle.net/1942/33027
Title: | Adjusting win statistics for dependent censoring | Authors: | Dong, GH Huang, B Wang, DL VERBEECK, Johan Wang, JZ Hoaglin, DC |
Issue Date: | 2021 | Publisher: | WILEY | Source: | PHARMACEUTICAL STATISTICS, 20(3), p. 440-450 | Abstract: | For composite outcomes whose components can be prioritized on clinical importance, the win ratio, the net benefit and the win odds apply that order in comparing patients pairwise to produce wins and subsequently win proportions. Because these three statistics are derived using the same win proportions and they test the same hypothesis of equal win probabilities in the two treatment groups, we refer to them as win statistics. These methods, particularly the win ratio and the net benefit, have received increasing attention in methodological research and in design and analysis of clinical trials. For time-to-event outcomes, however, censoring may introduce bias. Previous work has shown that inverse-probability-of-censoring weighting (IPCW) can correct the win ratio for bias from independent censoring. The present article uses the IPCW approach to adjust win statistics for dependent censoring that can be predicted by baseline covariates and/or time-dependent covariates (producing the CovIPCW-adjusted win statistics). Theoretically and with examples and simulations, we show that the CovIPCW-adjusted win statistics are unbiased estimators of treatment effect in the presence of dependent censoring. | Keywords: | Informative censoring;IPCW;net benefit;win odds;win ratio | Document URI: | http://hdl.handle.net/1942/33027 | ISSN: | 1539-1604 | e-ISSN: | 1539-1612 | DOI: | 10.1002/pst.2086 | ISI #: | 000593010400001 | Category: | A1 | Type: | Journal Contribution | Validations: | ecoom 2022 |
Appears in Collections: | Research publications |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
Pharmaceutical Statistics - 2020 - Dong - Adjusting win statistics for dependent censoring.pdf Restricted Access | Published version | 817.23 kB | Adobe PDF | View/Open Request a copy |
WEB OF SCIENCETM
Citations
19
checked on Jul 11, 2024
Page view(s)
40
checked on Sep 6, 2022
Download(s)
4
checked on Sep 6, 2022
Google ScholarTM
Check
Altmetric
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.