Replication Value Usage and its Performance for Large Sample Sizes - Commentary on Isager et al. (2025)

The Replication Value (RV_Cn) metric was introduced to help researchers prioritize studies for replication based on expected utility. While we welcome the introduction of this straightforward and systematic replication decision approach, we identify two limitations of the RV_Cn. First, when testing the “repeatability” of a study or systematically incorporating replication into a research workflow, the RV_Cn may not always be the most suitable metric to guide decisions. Use cases should consider the scope conditions of the metric. Second, the RV_Cn shows limited sensitivity in distinguishing between studies with large sample sizes. To address this, we propose a simple adjustment: a log transformation of the sample size component. This modification improves the metric’s discriminatory power for high-N studies and better aligns the (RV_Cn) with its intended purpose: guiding efficient and meaningful replication efforts.