论文标题
复制研究的功率计算
Power Calculations for Replication Studies
论文作者
论文摘要
可重复性危机导致正在进行的复制研究越来越多。基于原始研究的效果估计，通常使用条件能力来计算复制研究的样本量。但是，这种方法并不适合，因为它忽略了原始结果的不确定性。贝叶斯方法用于临床试验中，以将先前的信息纳入功率计算中。我们建议将此方法适应复制框架，并在复制研究设计中促进预测性而不是条件能力。此外，我们描述了如何将方法扩展到顺序临床试验的复制研究。比较了在临时分析中计算出的条件和预测能力，我们认为预测能力是决定是否过早停止复制研究的有用工具。关于社会科学的复制性的最新项目用于说明不同方法的属性。
The reproducibility crisis has led to an increasing number of replication studies being conducted. Sample sizes for replication studies are often calculated using conditional power based on the effect estimate from the original study. However, this approach is not well suited as it ignores the uncertainty of the original result. Bayesian methods are used in clinical trials to incorporate prior information into power calculations. We propose to adapt this methodology to the replication framework and promote the use of predictive instead of conditional power in the design of replication studies. Moreover, we describe how extensions of the methodology to sequential clinical trials can be tailored to replication studies. Conditional and predictive power calculated at an interim analysis are compared and we argue that predictive power is a useful tool to decide whether to stop a replication study prematurely. A recent project on the replicability of social sciences is used to illustrate the properties of the different methods.
