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Addressing selective reporting of experiments – the case for predefined exclusion criteria

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  • Neves, Kleber
  • Amaral, Olavo Bohrer

Abstract

Articles describing experimental data in the life sciences are meant to tell a clear story to the reader. This means that not every experimental attempt ends up published, as failed experiments and uninformative data are typically filtered out by researchers. Freedom to exclude data from an article, however, can lead to reporting bias when exclusion decisions are made after results are in. We discuss how to balance clarity and thoroughness in biomedical research reporting, and suggest that predefined criteria for experimental validity might help in solving this conflict.

Suggested Citation

  • Neves, Kleber & Amaral, Olavo Bohrer, 2019. "Addressing selective reporting of experiments – the case for predefined exclusion criteria," MetaArXiv a8gu5_v1, Center for Open Science.
    • Handle: RePEc:osf:metaar:a8gu5_v1
    DOI: 10.31219/osf.io/a8gu5_v1
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    References listed on IDEAS

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    1. Nosek, BA & Alter, G & Banks, GC & Borsboom, D & Bowman, SD & Breckler, SJ & Buck, S & Chambers, CD & Chin, G & Christensen, G & Contestabile, M & Dafoe, A & Eich, E & Freese, J & Glennerster, R & Gor, 2015. "Promoting an open research culture," Department of Economics, Working Paper Series qt7wh1000s, Department of Economics, Institute for Business and Economic Research, UC Berkeley.
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