NDLI: Empirical likelihood method for multivariate Cox regression

Content Provider	Springer Nature Link
Author	Zheng, Ming Yu, Wen
Copyright Year	2012
Abstract	A unified empirical likelihood approach for three Cox-type marginal models dealing with multiple event times, recurrent event times and clustered event times is proposed. The resulting log-empirical likelihood ratio test statistics are shown to possess chi-squared limiting distributions. When making inferences, there is no need to solve estimating equations nor to estimate limiting covariance matrices. The optimal linear combination property for over-identified empirical likelihood is preserved by the proposed method and the property can be used to improve estimation efficiency. In addition, an adjusted empirical likelihood approach is applied to reduce the error rates of the proposed empirical likelihood ratio tests. The adjusted empirical likelihood tests could outperform the existing Wald tests for small to moderate sample sizes. The proposed approach is illustrated by extensive simulation studies and two real examples.
Starting Page	1241
Ending Page	1267
Page Count	27
File Format	PDF
ISSN	09434062
Journal	Computational Statistics
Volume Number	28
Issue Number	3
e-ISSN	16139658
Language	English
Publisher	Springer-Verlag
Publisher Date	2012-08-17
Publisher Place	Berlin, Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Clustered event times Empirical likelihood Marginal model Multiple event times Over-identified Proportional hazards model Recurrent event times Statistics Probability and Statistics in Computer Science Probability Theory and Stochastic Processes Economic Theory
Content Type	Text
Resource Type	Article
Subject	Statistics and Probability Statistics, Probability and Uncertainty Computational Mathematics

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