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Initial evidence of research quality of registered reports compared with the standard publishing model

Author

Listed:
  • Courtney K. Soderberg

    (Center for Open Science)

  • Timothy M. Errington

    (Center for Open Science)

  • Sarah R. Schiavone

    (University of California, Davis)

  • Julia Bottesini

    (University of California, Davis)

  • Felix Singleton Thorn

    (University of Melbourne)

  • Simine Vazire

    (University of California, Davis
    University of Melbourne)

  • Kevin M. Esterling

    (University of California, Riverside)

  • Brian A. Nosek

    (Center for Open Science
    University of Virginia)

Abstract

In registered reports (RRs), initial peer review and in-principle acceptance occur before knowing the research outcomes. This combats publication bias and distinguishes planned from unplanned research. How RRs could improve the credibility of research findings is straightforward, but there is little empirical evidence. Also, there could be unintended costs such as reducing novelty. Here, 353 researchers peer reviewed a pair of papers from 29 published RRs from psychology and neuroscience and 57 non-RR comparison papers. RRs numerically outperformed comparison papers on all 19 criteria (mean difference 0.46, scale range −4 to +4) with effects ranging from RRs being statistically indistinguishable from comparison papers in novelty (0.13, 95% credible interval [−0.24, 0.49]) and creativity (0.22, [−0.14, 0.58]) to sizeable improvements in rigour of methodology (0.99, [0.62, 1.35]) and analysis (0.97, [0.60, 1.34]) and overall paper quality (0.66, [0.30, 1.02]). RRs could improve research quality while reducing publication bias and ultimately improve the credibility of the published literature.

Suggested Citation

  • Courtney K. Soderberg & Timothy M. Errington & Sarah R. Schiavone & Julia Bottesini & Felix Singleton Thorn & Simine Vazire & Kevin M. Esterling & Brian A. Nosek, 2021. "Initial evidence of research quality of registered reports compared with the standard publishing model," Nature Human Behaviour, Nature, vol. 5(8), pages 990-997, August.
    • Handle: RePEc:nat:nathum:v:5:y:2021:i:8:d:10.1038_s41562-021-01142-4
    DOI: 10.1038/s41562-021-01142-4
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    Cited by:

    1. Joel Ferguson & Rebecca Littman & Garret Christensen & Elizabeth Levy Paluck & Nicholas Swanson & Zenan Wang & Edward Miguel & David Birke & John-Henry Pezzuto, 2023. "Survey of open science practices and attitudes in the social sciences," Nature Communications, Nature, vol. 14(1), pages 1-13, December.
    2. Adler, Susanne Jana & Röseler, Lukas & Schöniger, Martina Katharina, 2023. "A toolbox to evaluate the trustworthiness of published findings," Journal of Business Research, Elsevier, vol. 167(C).
    3. Shaw, Steven D. & Nave, Gideon, 2023. "Don't hate the player, hate the game: Realigning incentive structures to promote robust science and better scientific practices in marketing," Journal of Business Research, Elsevier, vol. 167(C).
    4. UK Reproducibility Network Steering Committee, 2021. "From grassroots to global: A blueprint for building a reproducibility network," PLOS Biology, Public Library of Science, vol. 19(11), pages 1-6, November.
    5. Urs Fischbacher & Irenaeus Wolff, 2023. "Editorial: Symposium “Pre-results review”," Experimental Economics, Springer;Economic Science Association, vol. 26(3), pages 491-498, July.

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