Abstract

In this paper, we consider the empirical likelihood confidence intervals for mean difference under the assumption of missing at random (MAR). We prove that the empirical log-likelihood ratio of mean difference converges to a standard chi-squared distribution. We conduct simulation study to compare the proposed empirical likelihood with the normal approximation method in terms of the coverage accuracies and average lengths of confidence intervals. By Monte Carlo simulations, we verify that the proposed method performs well.

中文翻译：

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具有缺失数据的两个样本之间平均差异的经验似然

摘要

在本文中，我们在随机缺失 (MAR) 的假设下考虑平均差的经验似然置信区间。我们证明平均差的经验对数似然比收敛到标准卡方分布。我们进行了模拟研究，以在覆盖精度和置信区间的平均长度方面将所提出的经验似然与正态近似方法进行比较。通过蒙特卡罗模拟，我们验证了所提出的方法表现良好。