Non-parametric tests for right-censored data with biased sampling
Testing the equality of two survival distributions can be difficult in a prevalent cohort study when non-random sampling of subjects is involved. Owing to the biased sampling scheme, the independent censoring assumption is often violated. Although the issues about biased inference caused by length-biased sampling have been widely recognized in the statistical, epidemiological and economical literature, there is no satisfactory solution for efficient two-sample testing. We propose an asymptotic most efficient non-parametric test by properly adjusting for length-biased sampling. The test statistic is derived from a full likelihood function and can be generalized from the two-sample test to a "k"-sample test. The asymptotic properties of the test statistic under the null hypothesis are derived by using its asymptotic independent and identically distributed representation. We conduct extensive Monte Carlo simulations to evaluate the performance of the test statistics proposed and compare them with the conditional test and the standard log-rank test for various biased sampling schemes and right-censoring mechanisms. For length-biased data, empirical studies demonstrated that the test proposed is substantially more powerful than the existing methods. For general left-truncated data, the test proposed is robust, still maintains accurate control of the type I error rate and is also more powerful than the existing methods, if the truncation patterns and right censoring patterns are the same between the groups. We illustrate the methods by using two real data examples. Copyright (c) 2010 Royal Statistical Society.
If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
Volume (Year): 72 (2010)
Issue (Month): 5 ()
|Contact details of provider:|| Postal: 12 Errol Street, London EC1Y 8LX, United Kingdom|
Web page: http://wileyonlinelibrary.com/journal/rssb
More information through EDIRC
|Order Information:||Web: http://ordering.onlinelibrary.wiley.com/subs.asp?ref=1467-9868&doi=10.1111/(ISSN)1467-9868|
When requesting a correction, please mention this item's handle: RePEc:bla:jorssb:v:72:y:2010:i:5:p:609-630. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Wiley-Blackwell Digital Licensing)or (Christopher F. Baum)
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.