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概述：在本文中，我们比较两个以时间为基础的方法，这两个方法已被广泛用于治疗前后随机缺失数据的研究中来测试没有治疗效果的假设。我们的理论推导和模拟结果表明，基于所有可用的数据的方法并不比使用完整配对数据更有效。我们提出了一个合并这两个方法最佳的线性组合使其在所有案例中更有效。“,”Summary: In this paper we compare two moment-based methods which have been widely used to test the hypothesis of no treatment effect in pre- and post-treatment studies with data missing completely at random. Our theoretical derivation and simulation results show that the method based on all available data is not necessarily more effcient than the method that uses only complete data pairs. We propose an opitmal linear combinaiton of these two methods which turns to be more powerful in all cases.