Improving the efficiency of the log-rank test using auxiliary covariates
成果类型：
Article
署名作者：
Lu, Xiaomin; Tsiatis, Anastasios A.
署名单位：
State University System of Florida; University of Florida; North Carolina State University
刊物名称：
BIOMETRIKA
ISSN/ISSBN：
0006-3444
DOI：
10.1093/biomet/asn003
发表日期：
2008
页码：
679694
关键词：
摘要：
Under the assumption of proportional hazards, the log-rank test is optimal for testing the null hypothesis H-0 : beta = 0, where beta denotes the logarithm of the hazard ratio. However, if there are additional covariates that correlate with survival times, making use of their information will increase the efficiency of the log-rank test. We apply the theory of semiparametrics to characterize a class of regular and asymptotically linear estimators for beta when auxiliary covariates are incorporated into the model, and derive estimators that are more efficient. The Wald tests induced by these estimators are shown to be more powerful than the log-rank test. Simulation studies are used to illustrate the gains in efficiency.
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