Information bounds and nonparametric maximum likelihood estimation
Information bounds and nonparametric maximum likelihood estimation
Empirical likelihood based confidence intervals for copulas
Journal of Multivariate Analysis
Smoothed jackknife empirical likelihood method for ROC curve
Journal of Multivariate Analysis
Semiparametric inference for transformation models via empirical likelihood
Journal of Multivariate Analysis
Smoothed empirical likelihood for ROC curves with censored data
Journal of Multivariate Analysis
Empirical likelihood inferences for the semiparametric additive isotonic regression
Journal of Multivariate Analysis
Jackknife empirical likelihood tests for error distributions in regression models
Journal of Multivariate Analysis
Smoothed jackknife empirical likelihood inference for the difference of ROC curves
Journal of Multivariate Analysis
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For regression analysis of interval-censored failure time data, Zhang et al. (2005) [40] proposed an estimating equation approach to fit linear transformation models. In this paper, we develop two empirical likelihood (EL) inference approaches for the regression parameters based on the generalized estimating equations. The limiting distributions of log-empirical likelihood ratios are derived and empirical likelihood confidence intervals for any specified component of regression parameters are obtained. We carry out extensive simulation studies to compare the proposed methods with the method discussed by Zhang et al. (2005) [40]. The simulation results demonstrate that the EL and jackknife EL methods for linear transformation models have better performance than the existing normal approximation method based on coverage probability of confidence intervals in most cases, and they enable us to overcome an under-coverage problem for the confidence intervals of the regression parameters using a normal approximation when sample sizes are small and right censoring is heavy. Two real data examples are provided to illustrate our procedures.