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Predicting Replication Rates with Z-Curve: A Brief Exploratory Validation Study Using the Replication Database

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  • Röseler, Lukas

    (University of Münster)

Abstract

Concerns of replicability are widespread in the social sciences. As it is not feasible to replicate every published study, researchers have been developing methods to estimate replicability. I used the Replication Database (Röseler et al., 2023) to compare actual replication rates with replicability estimates provided by z-curve. After drawing stratified samples with actual replication rates that were uniformly distributed, z-curve’s replicability estimates had lower variance but correlated strongly with actual replicability rates, r = .933. Using a linear model, predicted replication rates deviated from actual replication rates by <±16% when samples from 322 studies (2.5 and 97.5% quantiles) were drawn. I propose that z-curve is a valid and economic method to compare replicability estimates for large sets of studies. Future studies of moderators in the context of z-curve or replicability should be tested using replication databases. The study’s code and data are available online (https://osf.io/k4d6w/).

Suggested Citation

  • Röseler, Lukas, 2023. "Predicting Replication Rates with Z-Curve: A Brief Exploratory Validation Study Using the Replication Database," MetaArXiv ewb2t_v1, Center for Open Science.
    • Handle: RePEc:osf:metaar:ewb2t_v1
    DOI: 10.31219/osf.io/ewb2t_v1
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    1. Röseler, Lukas & Gendlina, Taisia & Krapp, Josefine & Labusch, Noemi & Schütz, Astrid, 2022. "Successes and Failures of Replications: A Meta-Analysis of Independent Replication Studies Based on the OSF Registries," MetaArXiv 8psw2, Center for Open Science.
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