Given recent evidence challenging the replicability of results in the social and behavioral sciences, critical questions have been raised about appropriate measures for determining replication success in comparing effect estimates across studies. At issue is the fact that conclusions about replication success often depend on the measure used for evaluating correspondence in results. Despite the importance of choosing an appropriate measure, there is still no widespread agreement about which measures should be used. This article addresses these questions by describing formally the most commonly used measures for assessing replication success, and by comparing their performance in different contexts according to their replication probabilities-that is, the probability of obtaining replication success given study-specific settings. The measures may be characterized broadly as conclusion-based approaches, which assess the congruence of two independent studies' conclusions about the presence of an effect, and distance-based approaches, which test for a significant difference or equivalence of two effect estimates. We also introduce a new measure for assessing replication success called the correspondence test, which combines a difference and equivalence test in the same framework. To help researchers plan prospective replication efforts, we provide closed formulas for power calculations that can be used to determine the minimum detectable effect size (and thus, sample sizes) for each study so that a predetermined minimum replication probability can be achieved. Finally, we use a replication data set from the Open Science Collaboration (2015) to demonstrate the extent to which conclusions about replication success depend on the correspondence measure selected. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

中文翻译：

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用于评估复制成功的对应措施。

鉴于最近的证据对社会和行为科学结果的可重复性提出了挑战，人们对在比较不同研究的效果估计时确定重复成功的适当措施提出了关键问题。问题在于，关于复制成功的结论通常取决于用于评估结果对应性的衡量标准。尽管选择适当的措施很重要，但对于应该使用哪些措施仍然没有达成广泛的共识。本文通过正式描述评估复制成功的最常用衡量标准，并根据复制概率（即在特定研究设置下获得复制成功的概率）比较它们在不同环境中的表现来解决这些问题。这些措施可以广泛地分为基于结论的方法和基于距离的方法，前者评估两项独立研究关于效果存在的结论的一致性，后者测试两个效果估计的显着差异或等效性。我们还引入了一种评估复制成功的新方法，称为对应测试，它将差异测试和等效测试结合在同一框架中。为了帮助研究人员规划预期的复制工作，我们提供了功效计算的封闭公式，可用于确定每项研究的最小可检测效应大小（以及样本大小），以便实现预定的最小复制概率。最后，我们使用开放科学合作组织（2015）的复制数据集来证明有关复制成功的结论在多大程度上取决于所选的对应性度量。（PsycInfo 数据库记录 (c) 2023 APA，保留所有权利）。