Empirical Likelihood in Survival Analysis

Since the pioneer work of Thomas & Grunkemeier (1975) and Owen (1988), empirical likelihood has been developed as a powerful nonparametric inference approach and become popular in statistical literature. There are many applications of empirical likelihood in survival analysis. In this paper, we present an overview of recent developments of empirical likelihood methods for survival data. In particular, we discuss empirical likelihood results for a general mean functional of the distribution function, a functional of the hazard function, the Cox proportional hazards model, and a semiparametric accelerated failure time model.