Empirical Likelihood Inference of Linear Transformation Models with Right Censored Data

摘要：

This article develops empirical inference method for linear transformation models with randomly right censored data. An empirical likelihood ratio statistic is constructed through a synthetic data approach and is shown to have a limiting weighted chi-square distribution. For inference convenience, an adjusted empirical likelihood ratio statistic is proposed on base of the former one, which is shown to have a limiting standard central chi-square distribution. Confidence regions of regression parameters are then constructed. A simulation study is carried out to investigate the performance of the empirical likelihood method and the adjusted empirical likelihood method proposed in this article compared with the traditional normal approximation method. It results out that the two empirical likelihood methods have more accurate confidence regions and better coverage probabilities than normal approximation method.

关键词： Transformation Model Inference Region Right Censoring Empirical Likelihood

作者: SUN Zhimeng ZHANG Zhongzhan

作者单位: College of Applied Sciences, Beijing University of Technology, P.R.China, 100124

会议类型: 国际会议

会议名称: 2009 International Institute of Applied Statistics Studies(2009 国际应用统计学术研讨会)

会议地点: 青岛

会议语种:英文

页码: 1-7

在线出版日期: 2009-07-25（万方平台首次上网日期，不代表论文的发表时间）