Abstract In this paper, we develop a Mean Empirical Likelihood (MeanEL) method for right censored data. This MeanEL approach is based on traditional empirical likelihood methods but uses synthetic data to construct an EL ratio statistics, which is shown to have a χ 2 limiting distribution. Different simulation studies show that the MeanEL confidence intervals tend to have more accurate coverage probabilities than other existing Empirical Likelihood methods. Theoretical comparisons of different EL methods are also provided under a general framework.

中文翻译：

---

基于合成右删失数据的经验似然

摘要在本文中，我们为右删失数据开发了一种平均经验似然（Mean Empirical Likelihood，MeanEL）方法。这种 MeanEL 方法基于传统的经验似然方法，但使用合成数据来构建 EL 比率统计数据，该统计数据显示具有 χ 2 极限分布。不同的模拟研究表明，与其他现有的经验似然方法相比，MeanEL 置信区间往往具有更准确的覆盖概率。在一般框架下还提供了不同 EL 方法的理论比较。