Empirical likelihood-based inference in linear models with interval censored data

An empirical likelihood approach to estimate the coefficients in linear model with interval censored responses is developed in this paper. By constructing unbiased transformation of interval censored data, an empirical log-likelihood function with asymptotic χ2 is derived. The confidence regions for the coefficients are constructed. Some simulation results indicate that the method performs better than the normal approximation method in term of coverage accuracies. © 2005 Springer Verlag.