Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/29603
Title: A new class of generalized log rank tests for interval-censored failure time data
Authors: Zhao, X 
Duan, R
Zhao, Q
Sun, J
Keywords: Asymptotic distribution
Clinical trials
Interval-censoring
Survival comparison
Issue Date: 2013
Publisher: Elsevier Science Bv
Source: Computational statistics and data analysis, 2013, v. 60, no. 1, p. 123-131 How to cite?
Journal: Computational Statistics and Data Analysis 
Abstract: This paper discusses nonparametric comparison of survival functions when one observes only interval-censored failure time data (Peto and Peto, 1972; Sun, 2006; Zhao et al.; 2008). For the problem, a few procedures have been proposed in the literature. However, most of the existing test procedures determine the test results or p-values based on ad hoc methods or the permutation approach. Furthermore for the test procedures whose asymptotic distributions have been derived, the results are only for the null hypothesis. In other words, no nonparametric test procedure exists that has a known asymptotic distribution under the alternative hypothesis and thus can be employed to carry out the power and test size calculation. In this paper, a new class of generalized log-rank tests is proposed and their asymptotic distributions are derived under both null and alternative hypotheses. A simulation study is conducted to assess their performance for finite sample situations and an illustrative example is provided.
URI: http://hdl.handle.net/10397/29603
ISSN: 0167-9473
DOI: 10.1016/j.csda.2012.11.002
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