Empirical likelihood semiparametric regression analysis under random censorship

[摘要] This paper considers large sample inference for the regression parameter in a partly linear model for right censored data. We introduce an estimated empirical likelihood for the regression parameter and show that its limiting distribution is a mixture of central chi-squared distributions. A Monte Carlo method is proposed to approximate the limiting distribution. This enables one to make empirical likelihood-based inference for the regression parameter. We also develop an adjusted empirical likelihood method which only appeals to standard chi-square tables. Finite sample performance of the proposed methods is illustrated in a simulation study. (C) 2002 Elsevier Science (USA).

[发布日期] 2002-11-01

[关键词] empirical likelihood;partly linear model;product-limit estimator;random censorship