Inference for Cox’s regression models via adjusted empirical likelihood. (English) Zbl 1304.65094
Summary: The Cox’s regression model is one of the most popular tools used in survival analysis. Recently, G. Qin and B.-Y. Jing [Commun. Stat., Simulation Comput. 30, No. 1, 79–90 (2001; Zbl 1008.62692)] applied empirical likelihood to study it with the assumption that baseline hazard function is known. However, in the Cox’s regression model the baseline hazard function is unspecified. Thus, their method suffers from severe defect. In this paper, we apply a variant of plug-in empirical likelihood by estimating the cumulative baseline hazard function. Adjusted empirical likelihood (AEL) confidence regions for the vector of regression parameters are obtained. Furthermore, we conduct a simulation study to evaluate the performance of the proposed AEL method by comparing it with normal approximation (NA) based method. The simulation studies show that both methods produce comparable coverage probabilities. The proposed AEL method outperforms the NA method based on power analysis.
MSC:
| 62-08 | Computational methods for problems pertaining to statistics |
Keywords:
confidence region; adjusted empirical likelihood; normal approximation; coverage probability; power analysisCitations:
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