Several scientific fields including psychology are undergoing a replication crisis. There are many reasons for this problem, one of which is a misuse of p-values. There are several alternatives to p-values, and in this paper we describe a complement that is geared towards replication. In particular, we focus on confidence intervals for the probability that a parameter estimate will exceed a specified value in an exact replication study. These intervals convey uncertainty in a way that p-values and standard confidence intervals do not, and can help researchers to draw sounder scientific conclusions. After briefly reviewing background on p-values and a few alternatives, we describe our approach and provide examples with simulated and real data. For linear models, we also describe how confidence intervals for the exceedance probability are related to p-values and confidence intervals for parameters.

中文翻译：

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以超过概率的置信区间实现可复制性

包括心理学在内的几个科学领域正在经历复制危机。造成此问题的原因有很多，其中之一是滥用 p 值。p 值有多种替代方法，在本文中，我们描述了一个面向复制的补充。特别是，我们关注参数估计将超过精确复制研究中指定值的概率的置信区间。这些区间以 p 值和标准置信区间所没有的方式传达不确定性，并且可以帮助研究人员得出更可靠的科学结论。在简要回顾了 p 值和一些替代方案的背景之后，我们描述了我们的方法并提供了带有模拟和真实数据的示例。对于线性模型，