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Z-curve 2.0: Estimating Replication Rates and Discovery Rates

Meta-Psychology (Växjö), 2022-09, Vol.6 [Peer Reviewed Journal]

2022. This work is published under https://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 2003-2714 ;EISSN: 2003-2714 ;DOI: 10.15626/MP.2021.2720

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  • Title:
    Z-curve 2.0: Estimating Replication Rates and Discovery Rates
  • Author: Bartoš, František ; Schimmack, Ulrich
  • Subjects: Confidence intervals
  • Is Part Of: Meta-Psychology (Växjö), 2022-09, Vol.6
  • Description: Selection for statistical significance is a well-known factor that distorts the published literature and challenges the cumulative progress in science. Recent replication failures have fueled concerns that many published results are false-positives. Brunner and Schimmack (2020) developed z-curve, a method for estimating the expected replication rate (ERR) – the predicted success rate of exact replication studies based on the mean power after selection for significance. This article introduces an extension of this method, z-curve 2.0. The main extension is an estimate of the expected discovery rate (EDR) – the estimate of a proportion that the reported statistically significant results constitute from all conducted statistical tests. This information can be used to detect and quantify the amount of selection bias by comparing the EDR to the observed discovery rate (ODR; observed proportion of statistically significant results). In addition, we examined the performance of bootstrapped confidence intervals in simulation studies. Based on these results, we created robust confidence intervals with good coverage across a wide range of scenarios to provide information about the uncertainty in EDR and ERR estimates. We implemented the method in the zcurve R package (Bartoš & Schimmack, 2020).
  • Publisher: Växjö
  • Language: English
  • Identifier: ISSN: 2003-2714
    EISSN: 2003-2714
    DOI: 10.15626/MP.2021.2720
  • Source: DOAJ Directory of Open Access Journals
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