Empirical likelihood inference for a semiparametric hazards regression model

• Published in: Communications in statistics. Theory and methods Vol. 45; no. 11; pp. 3236 - 3248
• Main Authors: Chen, Wei, Wang, Dehui
• Format: Journal Article
• Language: English
• Published: Philadelphia Taylor & Francis 02.06.2016; Taylor & Francis Ltd
• Subjects: Accelerated failure time model; Chi-square test; Confidence intervals; Confidence region; Degrees of freedom; Economic models; Empirical analysis; Empirical likelihood ratio; Estimating techniques; Hazards; Independent variables; Inference; Likelihood ratio; Mathematical analysis; Mathematical models; Normal approximation; Parameter estimation; Parameters; Primary: 62N02; Secondary: 62F25; Proportional hazards model; Random variables; Regression; Regression models; Right-censored data; Semiparametric regression; Statistical analysis; Statistical tests; Statistics
• ISSN: 0361-0926; 1532-415X
• DOI: 10.1080/03610926.2014.901368

We investigated the empirical likelihood inference approach under a general class of semiparametric hazards regression models with survival data subject to right-censoring. An empirical likelihood ratio for the full 2p regression parameters involved in the model is obtained. We showed that it converged weakly to a random variable which could be written as a weighted sum of 2p independent chi-squared variables with one degree of freedom. Using this, we could construct a confidence region for parameters. We also suggested an adjusted version for the preceding statistic, whose limit followed a standard chi-squared distribution with 2p degrees of freedom.