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Multi-lab replication projects such as Registered Replication Reports and Many Labs projects are used to replicate an effect in different labs. Data of these projects are usually analyzed using conventional meta-analysis methods. This is certainly not the best approach, because it does not make optimal use of the available data as summary data are analyzed rather than the participant data. I propose to analyze data of multi-lab replication projects by using individual participant data (IPD) meta-analysis where the participant data are analyzed directly. Two important advantages of IPD meta-analysis are that it generally has larger statistical power to detect moderator effects and allows drawing conclusions regarding moderators at the participant rather than lab level. I illustrate IPD meta-analysis using the published Registered Replication Report by McCarthy et al. (2018) and provide R code and offer recommendations to facilitate researchers to apply these methods to their own data.
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